---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18940'
abstract:
- lang: eng
text: BMP signaling has a conserved function in patterning the dorsal-ventral body
axis in Bilateria and the directive axis in anthozoan cnidarians. So far, cnidarian
studies have focused on the role of different BMP signaling network components
in regulating pSMAD1/5 gradient formation. Much less is known about the target
genes downstream of BMP signaling. To address this, we generated a genome-wide
list of direct pSMAD1/5 target genes in the anthozoan Nematostella
vectensis, several of which were conserved in Drosophila
and Xenopus. Our ChIP-seq analysis revealed that many
of the regulatory molecules with documented bilaterally symmetric expression in
Nematostella are directly controlled by BMP signaling.
We identified several so far uncharacterized BMP-dependent transcription factors
and signaling molecules, whose bilaterally symmetric expression may be indicative
of their involvement in secondary axis patterning. One of these molecules is zswim4-6,
which encodes a novel nuclear protein that can modulate the pSMAD1/5 gradient
and potentially promote BMP-dependent gene repression.
acknowledgement: This work was funded by the Austrian Science Foundation (FWF) grants
P26962-B21 and P32705-B to GG and by the European Research Council (ERC) under the
European Union’s Horizon 2020 research and innovation program (grant agreement No
637840 [QUANTPATTERN] and 863952 [ACE-OF-SPACE]) to PM. We thank Michaela Schwaiger,
Taras Kreslavsky, Hiromi Tagoh, and Patricio Ferrer Murguia for their help with
the ChIP protocol, Matthias Richter and Christian Hofer for their assistance with
in situ analyses, Emilio Gonzalez Morales for making the measurements for Figure
6—figure supplement 3, Catrin Weiler for the assistance in cloning zebrafish zswim5,
David Mörsdorf for critically reading the manuscript and help with data visualization,
and the Core Facility for Cell Imaging and Ultrastructure Research of the University
of Vienna for access to the confocal microscope.
article_processing_charge: Yes
article_type: original
author:
- first_name: Paul
full_name: Knabl, Paul
last_name: Knabl
- first_name: Alexandra
full_name: Schauer, Alexandra
id: 30A536BA-F248-11E8-B48F-1D18A9856A87
last_name: Schauer
orcid: 0000-0001-7659-9142
- first_name: Autumn P
full_name: Pomreinke, Autumn P
last_name: Pomreinke
- first_name: Bob
full_name: Zimmermann, Bob
last_name: Zimmermann
- first_name: Katherine W
full_name: Rogers, Katherine W
last_name: Rogers
- first_name: Daniel
full_name: Čapek, Daniel
last_name: Čapek
- first_name: Patrick
full_name: Müller, Patrick
last_name: Müller
- first_name: Grigory
full_name: Genikhovich, Grigory
last_name: Genikhovich
citation:
ama: Knabl P, Schauer A, Pomreinke AP, et al. Analysis of SMAD1/5 target genes in
a sea anemone reveals ZSWIM4-6 as a novel BMP signaling modulator. eLife.
2024;13. doi:10.7554/elife.80803
apa: Knabl, P., Schauer, A., Pomreinke, A. P., Zimmermann, B., Rogers, K. W., Čapek,
D., … Genikhovich, G. (2024). Analysis of SMAD1/5 target genes in a sea anemone
reveals ZSWIM4-6 as a novel BMP signaling modulator. ELife. eLife Sciences
Publications. https://doi.org/10.7554/elife.80803
chicago: Knabl, Paul, Alexandra Schauer, Autumn P Pomreinke, Bob Zimmermann, Katherine
W Rogers, Daniel Čapek, Patrick Müller, and Grigory Genikhovich. “Analysis of
SMAD1/5 Target Genes in a Sea Anemone Reveals ZSWIM4-6 as a Novel BMP Signaling
Modulator.” ELife. eLife Sciences Publications, 2024. https://doi.org/10.7554/elife.80803.
ieee: P. Knabl et al., “Analysis of SMAD1/5 target genes in a sea anemone
reveals ZSWIM4-6 as a novel BMP signaling modulator,” eLife, vol. 13. eLife
Sciences Publications, 2024.
ista: Knabl P, Schauer A, Pomreinke AP, Zimmermann B, Rogers KW, Čapek D, Müller
P, Genikhovich G. 2024. Analysis of SMAD1/5 target genes in a sea anemone reveals
ZSWIM4-6 as a novel BMP signaling modulator. eLife. 13.
mla: Knabl, Paul, et al. “Analysis of SMAD1/5 Target Genes in a Sea Anemone Reveals
ZSWIM4-6 as a Novel BMP Signaling Modulator.” ELife, vol. 13, eLife Sciences
Publications, 2024, doi:10.7554/elife.80803.
short: P. Knabl, A. Schauer, A.P. Pomreinke, B. Zimmermann, K.W. Rogers, D. Čapek,
P. Müller, G. Genikhovich, ELife 13 (2024).
date_created: 2025-01-29T08:48:34Z
date_published: 2024-02-07T00:00:00Z
date_updated: 2025-01-29T08:56:21Z
day: '07'
ddc:
- '570'
department:
- _id: CaHe
doi: 10.7554/elife.80803
file:
- access_level: open_access
checksum: 24548a184215d3f4547bba535ccfd7b1
content_type: application/pdf
creator: dernst
date_created: 2025-01-29T08:50:18Z
date_updated: 2025-01-29T08:50:18Z
file_id: '18941'
file_name: 2024_eLife_Knabl.pdf
file_size: 11855972
relation: main_file
success: 1
file_date_updated: 2025-01-29T08:50:18Z
fulldoi: https://doi.org/10.7554/elife.80803
has_accepted_license: '1'
intvolume: ' 13'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
publication: eLife
publication_identifier:
issn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: Analysis of SMAD1/5 target genes in a sea anemone reveals ZSWIM4-6 as a novel
BMP signaling modulator
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18944'
abstract:
- lang: eng
text: 'Understanding connectivity patterns exhibited by endangered species living
in fragmented habitats is fundamental to improving management and conservation
actions. Such improvements can be particularly pressing at the trailing edges
of these habitats, where populations are facing the greatest challenges from climate
change, and appear even more crucial if the species is commercially harvested.
Seascape genetics have been increasingly used to meet these needs. In this study,
we examined connectivity patterns among 32 populations of the oarweed kelp Laminaria
digitata located at the species’ southern range limit. The distance
(or sampling gap) between neighboring populations ranged from a few km to a few
100s of km. By genotyping 11 microsatellite markers, we aimed to (1) refine analyses
of population structure; (2) test whether on-shelf islands are genetically more
differentiated than mainland populations; (3) evaluate the relative importance
of various abiotic conditions in shaping the genetic structure; and (4) evaluate
if the relative importance of each environmental factor varied according to sampling
schemes. Our analyses revealed a positive relationship between connectivity links
and genetic diversity: populations with high levels of connectivity were genetically
enriched while isolated populations showed signs of genetic erosion. The genetically
impoverished populations corresponded to the southernmost populations as well
as populations along the northern coast of Brittany (Locquirec, Saint-Malo Bay)
and the northernmost population in Pas-de-Calais. By performing distance-based
redundancy analysis on various sampling schemes, geographic distance appeared
as the dominant factor influencing connectivity between populations separated
by great distances, while hydrodynamic processes were the main factor when analyzing
at a final spatial resolution.'
article_processing_charge: No
article_type: original
author:
- first_name: Louise
full_name: Fouqueau, Louise
id: 1676e173-8143-11ed-8927-fe165216a93f
last_name: Fouqueau
orcid: 0000-0003-0371-9339
- first_name: L
full_name: Reynes, L
last_name: Reynes
- first_name: F
full_name: Tempera, F
last_name: Tempera
- first_name: T
full_name: Bajjouk, T
last_name: Bajjouk
- first_name: A
full_name: Blanfuné, A
last_name: Blanfuné
- first_name: C
full_name: Chevalier, C
last_name: Chevalier
- first_name: M
full_name: Laurans, M
last_name: Laurans
- first_name: S
full_name: Mauger, S
last_name: Mauger
- first_name: M
full_name: Sourisseau, M
last_name: Sourisseau
- first_name: J
full_name: Assis, J
last_name: Assis
- first_name: L
full_name: Lévêque, L
last_name: Lévêque
- first_name: M
full_name: Valero, M
last_name: Valero
citation:
ama: Fouqueau L, Reynes L, Tempera F, et al. Seascape genetic study on Laminaria
digitata underscores the critical role of sampling schemes. Marine Ecology
Progress Series. 2024;740:23-42. doi:10.3354/meps14640
apa: Fouqueau, L., Reynes, L., Tempera, F., Bajjouk, T., Blanfuné, A., Chevalier,
C., … Valero, M. (2024). Seascape genetic study on Laminaria digitata underscores
the critical role of sampling schemes. Marine Ecology Progress Series.
Inter-Research Science Center. https://doi.org/10.3354/meps14640
chicago: Fouqueau, Louise, L Reynes, F Tempera, T Bajjouk, A Blanfuné, C Chevalier,
M Laurans, et al. “Seascape Genetic Study on Laminaria Digitata Underscores the
Critical Role of Sampling Schemes.” Marine Ecology Progress Series. Inter-Research
Science Center, 2024. https://doi.org/10.3354/meps14640.
ieee: L. Fouqueau et al., “Seascape genetic study on Laminaria digitata underscores
the critical role of sampling schemes,” Marine Ecology Progress Series,
vol. 740. Inter-Research Science Center, pp. 23–42, 2024.
ista: Fouqueau L, Reynes L, Tempera F, Bajjouk T, Blanfuné A, Chevalier C, Laurans
M, Mauger S, Sourisseau M, Assis J, Lévêque L, Valero M. 2024. Seascape genetic
study on Laminaria digitata underscores the critical role of sampling schemes.
Marine Ecology Progress Series. 740, 23–42.
mla: Fouqueau, Louise, et al. “Seascape Genetic Study on Laminaria Digitata Underscores
the Critical Role of Sampling Schemes.” Marine Ecology Progress Series,
vol. 740, Inter-Research Science Center, 2024, pp. 23–42, doi:10.3354/meps14640.
short: L. Fouqueau, L. Reynes, F. Tempera, T. Bajjouk, A. Blanfuné, C. Chevalier,
M. Laurans, S. Mauger, M. Sourisseau, J. Assis, L. Lévêque, M. Valero, Marine
Ecology Progress Series 740 (2024) 23–42.
corr_author: '1'
date_created: 2025-01-29T09:09:10Z
date_published: 2024-07-25T00:00:00Z
date_updated: 2025-01-29T09:12:34Z
day: '25'
department:
- _id: NiBa
doi: 10.3354/meps14640
fulldoi: https://doi.org/10.3354/meps14640
intvolume: ' 740'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://inria.hal.science/hal-04624490/
month: '07'
oa: 1
oa_version: Submitted Version
page: 23-42
publication: Marine Ecology Progress Series
publication_identifier:
eissn:
- 1616-1599
issn:
- 0171-8630
publication_status: published
publisher: Inter-Research Science Center
quality_controlled: '1'
scopus_import: '1'
status: public
title: Seascape genetic study on Laminaria digitata underscores the critical role
of sampling schemes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 740
year: '2024'
...
---
OA_type: closed access
_id: '18945'
abstract:
- lang: eng
text: Vaccinia-related kinase 1 (VRK1) and the δ and ε isoforms of casein kinase
1 (CK1) are linked to various disease-relevant pathways. However, the lack of
tool compounds for these kinases has significantly hampered our understanding
of their cellular functions and therapeutic potential. Here, we describe the structure-based
development of potent inhibitors of VRK1, a kinase highly expressed in various
tumor types and crucial for cell proliferation and genome integrity. Kinome-wide
profiling revealed that our compounds also inhibit CK1δ and CK1ε. We demonstrate
that dihydropteridinones 35 and 36 mimic the cellular outcomes of VRK1 depletion.
Complementary studies with existing CK1δ and CK1ε inhibitors suggest that these
kinases may play overlapping roles in cell proliferation and genome instability.
Together, our findings highlight the potential of VRK1 inhibition in treating
p53-deficient tumors and possibly enhancing the efficacy of existing cancer therapies
that target DNA stability or cell division.
acknowledgement: "R.M.C. and K.B.M. are grateful for support by FAPESP (Fundação de
Amparo à Pesquisa do Estado de São Paulo) (grants 2013/50724–5 and 2014/50897–0),
Embrapii (Empresa Brasileira de Pesquisa e Inovação Industrial), CNPq (Conselho
Nacional de Desenvolvimento Científico e Tecnológico) (grant 465651/2014–3) and
Aché Laboratórios Farmacêuticos. R.M.C. and O.G. are also grateful for support by
the Structural Genomics Consortium, a registered charity (1097737) that receives
funds from AbbVie, Bayer AG, Boehringer Ingelheim, Canada Foundation for Innovation,
Eshelman Institute for Innovation, Genentech, Genome Canada through the Ontario
Genomics Institute (OGI-196), EU/EFPIA/OICR/McGill/KTH/Diamond, Innovative Medicines
Initiative 2 Joint Undertaking (EUbOPEN Grant 875510), Janssen, Merck KGaA, Merck
& Co., Pfizer, Takeda, and Wellcome. B.L. and M.H. are grateful for support from
the Swedish Research Council, Swedish Cancer Society, Karolinska Institutet and
The Mark Foundation for Cancer Research. R.A.M.S. (2016/25320–6 and 2018/23322–7),
A.S.S. (2019/14275–8), S.N.S.V (2018/09475–5), V.M.A. (2022/00743–2) and M.R.C.
(2021/04853–4) were recipients of fellowships from the Fundação de Amparo à Pesquisa
do Estado de São Paulo, FAPESP. C.V.R. (88887.146077/2017–00), J.E.T. (88887.373547/2019–00)
and P.Z.R (88887.136432/2017–00) were the recipient of fellowships from the Coordenação
de Aperfeiçoamento de Pessoal de Nível Superior, CAPES.\r\nWe thank all members
of CQMED-UNICAMP for their help and support. We thank the staff of the Life Sciences
Core Facility (LaCTAD) at UNICAMP for the Genomics and Mass Spectrometry analysis.
We thank the NMR facility at UNICAMP Chemistry Institute for its assistance. We
thank the staff at the Northeastern Collaborative Access Team beamlines, which are
funded by the National Institute of General Medical Sciences from the National Institutes
of Health (P41 GM103403). The Pilatus 6M detector on the 24-ID-C beamline is funded
by a NIH-ORIP HEI grant (S10 RR029205). This research used resources of the Advanced
Photon Source; a U.S. Department of Energy (DOE) Office of Science User Facility
operated for the DOE Office of Science by Argonne National Laboratory under Contract
No. DE-AC02-06CH11357. We thank Diamond Light Source for access to beamline I24.
The authors thank Tammy Havener (SGC-UNC), Abid Hussain Sayyid (KI), and Yiqiu Yang
(KI) for valuable discussions and technical support."
article_processing_charge: No
article_type: original
author:
- first_name: Fernando H.
full_name: de Souza Gama, Fernando H.
last_name: de Souza Gama
- first_name: Luiz A.
full_name: Dutra, Luiz A.
last_name: Dutra
- first_name: Michael
full_name: Hawgood, Michael
last_name: Hawgood
- first_name: Caio Vinícius
full_name: dos Reis, Caio Vinícius
last_name: dos Reis
- first_name: Ricardo A. M.
full_name: Serafim, Ricardo A. M.
last_name: Serafim
- first_name: Marcos A.
full_name: Ferreira, Marcos A.
last_name: Ferreira
- first_name: Bruno V. M.
full_name: Teodoro, Bruno V. M.
last_name: Teodoro
- first_name: Jéssica Emi
full_name: Takarada, Jéssica Emi
last_name: Takarada
- first_name: André S.
full_name: Santiago, André S.
last_name: Santiago
- first_name: Dimitrios-Ilias
full_name: Balourdas, Dimitrios-Ilias
last_name: Balourdas
- first_name: Ann-Sofie
full_name: Nilsson, Ann-Sofie
last_name: Nilsson
- first_name: Bruno
full_name: Urien, Bruno
last_name: Urien
- first_name: Vitor M.
full_name: Almeida, Vitor M.
last_name: Almeida
- first_name: Carina
full_name: Gileadi, Carina
last_name: Gileadi
- first_name: Priscila Z.
full_name: Ramos, Priscila Z.
last_name: Ramos
- first_name: Anita P
full_name: Testa Salmazo, Anita P
id: 41F1F098-F248-11E8-B48F-1D18A9856A87
last_name: Testa Salmazo
- first_name: Stanley N. S.
full_name: Vasconcelos, Stanley N. S.
last_name: Vasconcelos
- first_name: Micael R.
full_name: Cunha, Micael R.
last_name: Cunha
- first_name: Susanne
full_name: Mueller, Susanne
last_name: Mueller
- first_name: Stefan
full_name: Knapp, Stefan
last_name: Knapp
- first_name: Katlin B.
full_name: Massirer, Katlin B.
last_name: Massirer
- first_name: Jonathan M.
full_name: Elkins, Jonathan M.
last_name: Elkins
- first_name: Opher
full_name: Gileadi, Opher
last_name: Gileadi
- first_name: Alessandra
full_name: Mascarello, Alessandra
last_name: Mascarello
- first_name: Bennie B. L. G.
full_name: Lemmens, Bennie B. L. G.
last_name: Lemmens
- first_name: Cristiano R. W.
full_name: Guimarães, Cristiano R. W.
last_name: Guimarães
- first_name: Hatylas
full_name: Azevedo, Hatylas
last_name: Azevedo
- first_name: Rafael M.
full_name: Couñago, Rafael M.
last_name: Couñago
citation:
ama: de Souza Gama FH, Dutra LA, Hawgood M, et al. Novel dihydropteridinone derivatives
as potent inhibitors of the understudied human kinases vaccinia-related kinase
1 and casein kinase 1δ/ε. Journal of Medicinal Chemistry. 2024;67(11):8609-8629.
doi:10.1021/acs.jmedchem.3c02250
apa: de Souza Gama, F. H., Dutra, L. A., Hawgood, M., dos Reis, C. V., Serafim,
R. A. M., Ferreira, M. A., … Couñago, R. M. (2024). Novel dihydropteridinone derivatives
as potent inhibitors of the understudied human kinases vaccinia-related kinase
1 and casein kinase 1δ/ε. Journal of Medicinal Chemistry. American Chemical
Society. https://doi.org/10.1021/acs.jmedchem.3c02250
chicago: Souza Gama, Fernando H. de, Luiz A. Dutra, Michael Hawgood, Caio Vinícius
dos Reis, Ricardo A. M. Serafim, Marcos A. Ferreira, Bruno V. M. Teodoro, et al.
“Novel Dihydropteridinone Derivatives as Potent Inhibitors of the Understudied
Human Kinases Vaccinia-Related Kinase 1 and Casein Kinase 1δ/ε.” Journal of
Medicinal Chemistry. American Chemical Society, 2024. https://doi.org/10.1021/acs.jmedchem.3c02250.
ieee: F. H. de Souza Gama et al., “Novel dihydropteridinone derivatives as
potent inhibitors of the understudied human kinases vaccinia-related kinase 1
and casein kinase 1δ/ε,” Journal of Medicinal Chemistry, vol. 67, no. 11.
American Chemical Society, pp. 8609–8629, 2024.
ista: de Souza Gama FH, Dutra LA, Hawgood M, dos Reis CV, Serafim RAM, Ferreira
MA, Teodoro BVM, Takarada JE, Santiago AS, Balourdas D-I, Nilsson A-S, Urien B,
Almeida VM, Gileadi C, Ramos PZ, Testa Salmazo AP, Vasconcelos SNS, Cunha MR,
Mueller S, Knapp S, Massirer KB, Elkins JM, Gileadi O, Mascarello A, Lemmens BBLG,
Guimarães CRW, Azevedo H, Couñago RM. 2024. Novel dihydropteridinone derivatives
as potent inhibitors of the understudied human kinases vaccinia-related kinase
1 and casein kinase 1δ/ε. Journal of Medicinal Chemistry. 67(11), 8609–8629.
mla: de Souza Gama, Fernando H., et al. “Novel Dihydropteridinone Derivatives as
Potent Inhibitors of the Understudied Human Kinases Vaccinia-Related Kinase 1
and Casein Kinase 1δ/ε.” Journal of Medicinal Chemistry, vol. 67, no. 11,
American Chemical Society, 2024, pp. 8609–29, doi:10.1021/acs.jmedchem.3c02250.
short: F.H. de Souza Gama, L.A. Dutra, M. Hawgood, C.V. dos Reis, R.A.M. Serafim,
M.A. Ferreira, B.V.M. Teodoro, J.E. Takarada, A.S. Santiago, D.-I. Balourdas,
A.-S. Nilsson, B. Urien, V.M. Almeida, C. Gileadi, P.Z. Ramos, A.P. Testa Salmazo,
S.N.S. Vasconcelos, M.R. Cunha, S. Mueller, S. Knapp, K.B. Massirer, J.M. Elkins,
O. Gileadi, A. Mascarello, B.B.L.G. Lemmens, C.R.W. Guimarães, H. Azevedo, R.M.
Couñago, Journal of Medicinal Chemistry 67 (2024) 8609–8629.
date_created: 2025-01-29T09:14:19Z
date_published: 2024-05-23T00:00:00Z
date_updated: 2025-01-29T09:19:15Z
day: '23'
department:
- _id: CaBe
doi: 10.1021/acs.jmedchem.3c02250
external_id:
pmid:
- '38780468'
fulldoi: https://doi.org/10.1021/acs.jmedchem.3c02250
intvolume: ' 67'
issue: '11'
language:
- iso: eng
month: '05'
oa_version: None
page: 8609-8629
pmid: 1
publication: Journal of Medicinal Chemistry
publication_identifier:
eissn:
- 1520-4804
issn:
- 0022-2623
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Novel dihydropteridinone derivatives as potent inhibitors of the understudied
human kinases vaccinia-related kinase 1 and casein kinase 1δ/ε
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 67
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18949'
abstract:
- lang: eng
text: 'Speciation research—the scientific field focused on understanding the origin
and diversity of species—has a long and complex history. While relevant to one
another, the specific goals and activities of speciation researchers are highly
diverse, and scattered across a collection of different perspectives. Thus, our
understanding of speciation will benefit from efforts to bridge scientific findings
and the diverse people who do the work. In this paper, we outline two ways of
integrating speciation research: (i) scientific integration, through the bringing
together of ideas, data, and approaches; and (ii) social integration, by creating
ways for a diversity of researchers to participate in the scientific process.
We then discuss five challenges to integration: (i) the multidisciplinary nature
of speciation research, (ii) the complex language of speciation; (iii) a bias
toward certain study systems; (iv) the challenges of working across scales; and
(v) inconsistent measures and reporting standards. We provide practical steps
that individuals and groups can take to help overcome these challenges, and argue
that integration is a team effort in which we all have a role to play.'
acknowledgement: "We thank the staff of the Tvärminne Zoological Station (University
of Helsinki) for their hospitality during the workshop. We are also grateful to
everyone who applied to attend the workshop.\r\nFunding for the workshop was provided
by the European Society for Evolutionary Biology through the Special Topic Network
(STN) funding scheme."
article_number: kzae001
article_processing_charge: Yes
article_type: original
author:
- first_name: Sean
full_name: Stankowski, Sean
id: 43161670-5719-11EA-8025-FABC3DDC885E
last_name: Stankowski
- first_name: Asher D
full_name: Cutter, Asher D
last_name: Cutter
- first_name: Ina
full_name: Satokangas, Ina
last_name: Satokangas
- first_name: Brian A
full_name: Lerch, Brian A
last_name: Lerch
- first_name: Jonathan
full_name: Rolland, Jonathan
last_name: Rolland
- first_name: Carole M
full_name: Smadja, Carole M
last_name: Smadja
- first_name: J Carolina
full_name: Segami Marzal, J Carolina
last_name: Segami Marzal
- first_name: Christopher R
full_name: Cooney, Christopher R
last_name: Cooney
- first_name: Philine G D
full_name: Feulner, Philine G D
last_name: Feulner
- first_name: Fabricius Maia Chaves Bicalho
full_name: Domingos, Fabricius Maia Chaves Bicalho
last_name: Domingos
- first_name: Henry L
full_name: North, Henry L
last_name: North
- first_name: Ryo
full_name: Yamaguchi, Ryo
last_name: Yamaguchi
- first_name: Roger K
full_name: Butlin, Roger K
last_name: Butlin
- first_name: Jochen B W
full_name: Wolf, Jochen B W
last_name: Wolf
- first_name: Jenn
full_name: Coughlan, Jenn
last_name: Coughlan
- first_name: Patrick
full_name: Heidbreder, Patrick
last_name: Heidbreder
- first_name: Rebeca
full_name: Hernández-Gutiérrez, Rebeca
last_name: Hernández-Gutiérrez
- first_name: Karen B
full_name: Barnard-Kubow, Karen B
last_name: Barnard-Kubow
- first_name: David
full_name: Peede, David
last_name: Peede
- first_name: Loïs
full_name: Rancilhac, Loïs
last_name: Rancilhac
- first_name: Rodrigo Brincalepe
full_name: Salvador, Rodrigo Brincalepe
last_name: Salvador
- first_name: Ken A
full_name: Thompson, Ken A
last_name: Thompson
- first_name: Elizabeth A
full_name: Stacy, Elizabeth A
last_name: Stacy
- first_name: Leonie C
full_name: Moyle, Leonie C
last_name: Moyle
- first_name: Martin D
full_name: Garlovsky, Martin D
last_name: Garlovsky
- first_name: Arif
full_name: Maulana, Arif
last_name: Maulana
- first_name: Annina
full_name: Kantelinen, Annina
last_name: Kantelinen
- first_name: N Ivalú
full_name: Cacho, N Ivalú
last_name: Cacho
- first_name: Hilde
full_name: Schneemann, Hilde
last_name: Schneemann
- first_name: Marisol
full_name: Domínguez, Marisol
last_name: Domínguez
- first_name: Erik B
full_name: Dopman, Erik B
last_name: Dopman
- first_name: Konrad
full_name: Lohse, Konrad
last_name: Lohse
- first_name: Sina J
full_name: Rometsch, Sina J
last_name: Rometsch
- first_name: Aaron A
full_name: Comeault, Aaron A
last_name: Comeault
- first_name: Richard M
full_name: Merrill, Richard M
last_name: Merrill
- first_name: Elizabeth S C
full_name: Scordato, Elizabeth S C
last_name: Scordato
- first_name: Sonal
full_name: Singhal, Sonal
last_name: Singhal
- first_name: Varpu
full_name: Pärssinen, Varpu
last_name: Pärssinen
- first_name: Alycia C R
full_name: Lackey, Alycia C R
last_name: Lackey
- first_name: Sanghamitra
full_name: Kumar, Sanghamitra
last_name: Kumar
- first_name: Joana I
full_name: Meier, Joana I
last_name: Meier
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Christelle
full_name: Fraisse, Christelle
id: 32DF5794-F248-11E8-B48F-1D18A9856A87
last_name: Fraisse
orcid: 0000-0001-8441-5075
- first_name: Mark
full_name: Ravinet, Mark
last_name: Ravinet
- first_name: Jonna
full_name: Kulmuni, Jonna
last_name: Kulmuni
citation:
ama: Stankowski S, Cutter AD, Satokangas I, et al. Toward the integration of speciation
research. Evolutionary Journal of the Linnean Society. 2024;3(1). doi:10.1093/evolinnean/kzae001
apa: Stankowski, S., Cutter, A. D., Satokangas, I., Lerch, B. A., Rolland, J., Smadja,
C. M., … Kulmuni, J. (2024). Toward the integration of speciation research. Evolutionary
Journal of the Linnean Society. Oxford University Press. https://doi.org/10.1093/evolinnean/kzae001
chicago: Stankowski, Sean, Asher D Cutter, Ina Satokangas, Brian A Lerch, Jonathan
Rolland, Carole M Smadja, J Carolina Segami Marzal, et al. “Toward the Integration
of Speciation Research.” Evolutionary Journal of the Linnean Society. Oxford
University Press, 2024. https://doi.org/10.1093/evolinnean/kzae001.
ieee: S. Stankowski et al., “Toward the integration of speciation research,”
Evolutionary Journal of the Linnean Society, vol. 3, no. 1. Oxford University
Press, 2024.
ista: Stankowski S, Cutter AD, Satokangas I, Lerch BA, Rolland J, Smadja CM, Segami
Marzal JC, Cooney CR, Feulner PGD, Domingos FMCB, North HL, Yamaguchi R, Butlin
RK, Wolf JBW, Coughlan J, Heidbreder P, Hernández-Gutiérrez R, Barnard-Kubow KB,
Peede D, Rancilhac L, Salvador RB, Thompson KA, Stacy EA, Moyle LC, Garlovsky
MD, Maulana A, Kantelinen A, Cacho NI, Schneemann H, Domínguez M, Dopman EB, Lohse
K, Rometsch SJ, Comeault AA, Merrill RM, Scordato ESC, Singhal S, Pärssinen V,
Lackey ACR, Kumar S, Meier JI, Barton NH, Fraisse C, Ravinet M, Kulmuni J. 2024.
Toward the integration of speciation research. Evolutionary Journal of the Linnean
Society. 3(1), kzae001.
mla: Stankowski, Sean, et al. “Toward the Integration of Speciation Research.” Evolutionary
Journal of the Linnean Society, vol. 3, no. 1, kzae001, Oxford University
Press, 2024, doi:10.1093/evolinnean/kzae001.
short: S. Stankowski, A.D. Cutter, I. Satokangas, B.A. Lerch, J. Rolland, C.M. Smadja,
J.C. Segami Marzal, C.R. Cooney, P.G.D. Feulner, F.M.C.B. Domingos, H.L. North,
R. Yamaguchi, R.K. Butlin, J.B.W. Wolf, J. Coughlan, P. Heidbreder, R. Hernández-Gutiérrez,
K.B. Barnard-Kubow, D. Peede, L. Rancilhac, R.B. Salvador, K.A. Thompson, E.A.
Stacy, L.C. Moyle, M.D. Garlovsky, A. Maulana, A. Kantelinen, N.I. Cacho, H. Schneemann,
M. Domínguez, E.B. Dopman, K. Lohse, S.J. Rometsch, A.A. Comeault, R.M. Merrill,
E.S.C. Scordato, S. Singhal, V. Pärssinen, A.C.R. Lackey, S. Kumar, J.I. Meier,
N.H. Barton, C. Fraisse, M. Ravinet, J. Kulmuni, Evolutionary Journal of the Linnean
Society 3 (2024).
corr_author: '1'
date_created: 2025-01-29T10:38:17Z
date_published: 2024-02-16T00:00:00Z
date_updated: 2025-01-29T10:55:54Z
day: '16'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1093/evolinnean/kzae001
file:
- access_level: open_access
checksum: db08120a92527acaef476bd93f2b87f9
content_type: application/pdf
creator: dernst
date_created: 2025-01-29T10:52:40Z
date_updated: 2025-01-29T10:52:40Z
file_id: '18950'
file_name: 2024_EvolJourLinneanSoc_Stankowski.pdf
file_size: 3935454
relation: main_file
success: 1
file_date_updated: 2025-01-29T10:52:40Z
fulldoi: https://doi.org/10.1093/evolinnean/kzae001
has_accepted_license: '1'
intvolume: ' 3'
issue: '1'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
publication: Evolutionary Journal of the Linnean Society
publication_identifier:
issn:
- 2752-938X
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Toward the integration of speciation research
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18955'
abstract:
- lang: eng
text: We give a simple proof that assuming the Exponential Time Hypothesis (ETH),
determining the winner of a Rabin game cannot be done in time 2o(k log k) · nO(1),
where k is the number of pairs of vertex subsets involved in the winning condition
and n is the vertex count of the game graph. While this result follows from the
lower bounds provided by Calude et al [SIAM J. Comp. 2022], our reduction is considerably
simpler and arguably provides more insight into the complexity of the problem.
In fact, the analogous lower bounds discussed by Calude et al, for solving Muller
games and multidimensional parity games, follow as simple corollaries of our approach.
Our reduction also highlights the usefulness of a certain pivot problem — Permutation
SAT — which may be of independent interest.
acknowledgement: This work is a part of projects CUTACOMBS (Ma. Pilipczuk), BOBR (Mi.
Pilipczuk), and VAMOS (K. S. Thejaswini) that have received funding from the European
Research Council (ERC) under the European Union's Horizon 2020 research and innovation
programme, grant agreements No 714704, 948057, and 101020093, respectively. Ma.
Pilipczuk is also partially supported by Polish National Science Centre SONATA BIS-12
grant number 2022/46/E/ST6/00143.
article_processing_charge: No
arxiv: 1
author:
- first_name: Antonio
full_name: Casares, Antonio
last_name: Casares
- first_name: Marcin
full_name: Pilipczuk, Marcin
last_name: Pilipczuk
- first_name: Michał
full_name: Pilipczuk, Michał
last_name: Pilipczuk
- first_name: Uéverton S.
full_name: Souza, Uéverton S.
last_name: Souza
- first_name: K. S.
full_name: Thejaswini, K. S.
id: 3807fb92-fdc1-11ee-bb4a-b4d8a431c753
last_name: Thejaswini
citation:
ama: 'Casares A, Pilipczuk M, Pilipczuk M, Souza US, Thejaswini KS. Simple and tight
complexity lower bounds for solving Rabin games. In: 2024 Symposium on Simplicity
in Algorithms. Society for Industrial and Applied Mathematics; 2024:160-167.
doi:10.1137/1.9781611977936.16'
apa: 'Casares, A., Pilipczuk, M., Pilipczuk, M., Souza, U. S., & Thejaswini,
K. S. (2024). Simple and tight complexity lower bounds for solving Rabin games.
In 2024 Symposium on Simplicity in Algorithms (pp. 160–167). Alexandria,
VA, United States: Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611977936.16'
chicago: Casares, Antonio, Marcin Pilipczuk, Michał Pilipczuk, Uéverton S. Souza,
and K. S. Thejaswini. “Simple and Tight Complexity Lower Bounds for Solving Rabin
Games.” In 2024 Symposium on Simplicity in Algorithms, 160–67. Society
for Industrial and Applied Mathematics, 2024. https://doi.org/10.1137/1.9781611977936.16.
ieee: A. Casares, M. Pilipczuk, M. Pilipczuk, U. S. Souza, and K. S. Thejaswini,
“Simple and tight complexity lower bounds for solving Rabin games,” in 2024
Symposium on Simplicity in Algorithms, Alexandria, VA, United States, 2024,
pp. 160–167.
ista: 'Casares A, Pilipczuk M, Pilipczuk M, Souza US, Thejaswini KS. 2024. Simple
and tight complexity lower bounds for solving Rabin games. 2024 Symposium on Simplicity
in Algorithms. SOSA: Symposium on Simplicity in Algorithms, 160–167.'
mla: Casares, Antonio, et al. “Simple and Tight Complexity Lower Bounds for Solving
Rabin Games.” 2024 Symposium on Simplicity in Algorithms, Society for Industrial
and Applied Mathematics, 2024, pp. 160–67, doi:10.1137/1.9781611977936.16.
short: A. Casares, M. Pilipczuk, M. Pilipczuk, U.S. Souza, K.S. Thejaswini, in:,
2024 Symposium on Simplicity in Algorithms, Society for Industrial and Applied
Mathematics, 2024, pp. 160–167.
conference:
end_date: 2024-01-10
location: Alexandria, VA, United States
name: 'SOSA: Symposium on Simplicity in Algorithms'
start_date: 2024-01-08
date_created: 2025-01-29T11:55:50Z
date_published: 2024-01-01T00:00:00Z
date_updated: 2025-04-14T07:55:54Z
day: '01'
department:
- _id: ToHe
doi: 10.1137/1.9781611977936.16
ec_funded: 1
external_id:
arxiv:
- '2310.20433'
fulldoi: https://doi.org/10.1137/1.9781611977936.16
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2310.20433
month: '01'
oa: 1
oa_version: Preprint
page: 160-167
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: 2024 Symposium on Simplicity in Algorithms
publication_identifier:
isbn:
- '9781611977936'
publication_status: published
publisher: Society for Industrial and Applied Mathematics
quality_controlled: '1'
scopus_import: '1'
status: public
title: Simple and tight complexity lower bounds for solving Rabin games
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18956'
abstract:
- lang: eng
text: 'Group Activity Recognition (GAR) aims to detect the activity performed by
multiple actors in a scene. Prior works model the spatio-temporal features based
on the RGB, optical flow or keypoint data types. On the contrary, our hypothesis
is that by only using the RGB data without temporality, the performance can be
maintained with a negligible loss in accuracy. To that end, we propose a novel
GAR technique for volleyball videos, DECOMPL, which consists of two complementary
branches. In the visual branch, it extracts the features using attention pooling.
In the coordinate branch, it considers the configuration of the players and extracts
the spatial information from the box coordinates. Moreover, we analyzed the Volleyball
dataset that the recent literature is mostly based on, and systematically reannotated
it to emphasize the group concept. Experimental results demonstrated the effectiveness
of the proposed model DECOMPL, which delivered the best/second best GAR performance
with the reannotations/original annotations among the comparable state-of-the-art
methods. Code and new annotations are available at GitHub: https://github.com/berkerdemirel/decompl'
article_processing_charge: No
arxiv: 1
author:
- first_name: Berker
full_name: Demirel, Berker
id: 8b4bc47f-3200-11ee-973b-8f0e7be21a9f
last_name: Demirel
- first_name: Huseyin
full_name: Ozkan, Huseyin
last_name: Ozkan
citation:
ama: 'Demirel B, Ozkan H. Decompl: Decompositional learning with attention pooling
for group activity recognition from a single volleyball image. In: 2024 IEEE
International Conference on Image Processing. IEEE; 2024:977-983. doi:10.1109/icip51287.2024.10647499'
apa: 'Demirel, B., & Ozkan, H. (2024). Decompl: Decompositional learning with
attention pooling for group activity recognition from a single volleyball image.
In 2024 IEEE International Conference on Image Processing (pp. 977–983).
Abu Dhabi, United Arab Emirates: IEEE. https://doi.org/10.1109/icip51287.2024.10647499'
chicago: 'Demirel, Berker, and Huseyin Ozkan. “Decompl: Decompositional Learning
with Attention Pooling for Group Activity Recognition from a Single Volleyball
Image.” In 2024 IEEE International Conference on Image Processing, 977–83.
IEEE, 2024. https://doi.org/10.1109/icip51287.2024.10647499.'
ieee: 'B. Demirel and H. Ozkan, “Decompl: Decompositional learning with attention
pooling for group activity recognition from a single volleyball image,” in 2024
IEEE International Conference on Image Processing, Abu Dhabi, United Arab
Emirates, 2024, pp. 977–983.'
ista: 'Demirel B, Ozkan H. 2024. Decompl: Decompositional learning with attention
pooling for group activity recognition from a single volleyball image. 2024 IEEE
International Conference on Image Processing. ICIP: International Conference on
Image Processing, 977–983.'
mla: 'Demirel, Berker, and Huseyin Ozkan. “Decompl: Decompositional Learning with
Attention Pooling for Group Activity Recognition from a Single Volleyball Image.”
2024 IEEE International Conference on Image Processing, IEEE, 2024, pp.
977–83, doi:10.1109/icip51287.2024.10647499.'
short: B. Demirel, H. Ozkan, in:, 2024 IEEE International Conference on Image Processing,
IEEE, 2024, pp. 977–983.
conference:
end_date: 2024-10-30
location: Abu Dhabi, United Arab Emirates
name: 'ICIP: International Conference on Image Processing'
start_date: 2024-10-27
corr_author: '1'
date_created: 2025-01-29T12:22:24Z
date_published: 2024-11-01T00:00:00Z
date_updated: 2025-09-09T12:13:12Z
day: '01'
department:
- _id: FrLo
doi: 10.1109/icip51287.2024.10647499
external_id:
arxiv:
- '2303.06439'
isi:
- '001442947000143'
fulldoi: https://doi.org/10.1109/icip51287.2024.10647499
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2303.06439
month: '11'
oa: 1
oa_version: Preprint
page: 977-983
publication: 2024 IEEE International Conference on Image Processing
publication_identifier:
eisbn:
- '9798350349399'
eissn:
- 2381-8549
publication_status: published
publisher: IEEE
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/berkerdemirel/decompl
status: public
title: 'Decompl: Decompositional learning with attention pooling for group activity
recognition from a single volleyball image'
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
year: '2024'
...
---
OA_place: repository
OA_type: hybrid
_id: '18957'
abstract:
- lang: eng
text: Sui Lutris is the first smart-contract platform to sustainably achieve sub-second
finality. It achieves this significant decrease by employing consensusless agreement
not only for simple payments but for a large variety of transactions. Unlike prior
work, Sui Lutris neither compromises expressiveness nor throughput and can run
perpetually without restarts. Sui Lutris achieves this by safely integrating consensuless
agreement with a high-throughput consensus protocol that is invoked out of the
critical finality path but ensures that when a transaction is at risk of inconsistent
concurrent accesses, its settlement is delayed until the total ordering is resolved.
Building such a hybrid architecture is especially delicate during reconfiguration
events, where the system needs to preserve the safety of the consensusless path
without compromising the long-term liveness of potentially misconfigured clients.
We thus develop a novel reconfiguration protocol, the first to provably show the
safe and efficient reconfiguration of a consensusless blockchain. Sui Lutris is
currently running in production and underpins the Sui smart-contract platform.
Combined with the use of Objects instead of accounts it enables the safe execution
of smart contracts that expose objects as a first-class resource. In our experiments
Sui Lutris achieves latency lower than 0.5 seconds for throughput up to 5,000
certificates per second (150k ops/s with transaction blocks), compared to the
state-of-the-art real-world consensus latencies of 3 seconds. Furthermore, it
gracefully handles validators crash-recovery and does not suffer visible performance
degradation during reconfiguration.
acknowledgement: 'This work is funded by MystenLabs. We thank the Mysten Labs Engineering
teams for valuable feedback broadly, and specifically Dmitry Perelman and Todd Fiala
for managing the implementation effort. A number of folks contributed to specific
aspects of the implementation of Sui Lutris (amongst many other contributions to
the overall blockchain): Francois Garillot, Laura Makdah, Mingwei Tian, Andrew Schran,
Sadhan Sood and William Smith implemented and optimized aspects of both Sui Lutris
and Narwhal / Bullshark consensus; Alonso de Gortari oversaw the cryptoeconomics
of the blockchain, and Emma Zhong, Ade Adepoju, Tim Zakia and Dario Russi designed
and implemented staking and gas mechanisms. Adam Welc designed several Move tools
and provided great feedback on the manuscript. We also extend our thanks to Patrick
Kuo, Ge Gao, Chris Li, and Arun Koshy for their work on the Sui Lutris SDK, clients,
and RPC layer; Kostas Chalkias, Jonas Lindstrøm, and Joy Wang built cryptographic
components.'
article_processing_charge: No
arxiv: 1
author:
- first_name: Sam
full_name: Blackshear, Sam
last_name: Blackshear
- first_name: Andrey
full_name: Chursin, Andrey
last_name: Chursin
- first_name: George
full_name: Danezis, George
last_name: Danezis
- first_name: Anastasios
full_name: Kichidis, Anastasios
last_name: Kichidis
- first_name: Eleftherios
full_name: Kokoris Kogias, Eleftherios
id: f5983044-d7ef-11ea-ac6d-fd1430a26d30
last_name: Kokoris Kogias
- first_name: Xun
full_name: Li, Xun
last_name: Li
- first_name: Mark
full_name: Logan, Mark
last_name: Logan
- first_name: Ashok
full_name: Menon, Ashok
last_name: Menon
- first_name: Todd
full_name: Nowacki, Todd
last_name: Nowacki
- first_name: Alberto
full_name: Sonnino, Alberto
last_name: Sonnino
- first_name: Brandon
full_name: Williams, Brandon
last_name: Williams
- first_name: Lu
full_name: Zhang, Lu
last_name: Zhang
citation:
ama: 'Blackshear S, Chursin A, Danezis G, et al. Sui Lutris: A blockchain combining
broadcast and consensus. In: Proceedings of the 2024 on ACM SIGSAC Conference
on Computer and Communications Security. ACM; 2024:2606-2620. doi:10.1145/3658644.3670286'
apa: 'Blackshear, S., Chursin, A., Danezis, G., Kichidis, A., Kokoris Kogias, E.,
Li, X., … Zhang, L. (2024). Sui Lutris: A blockchain combining broadcast and consensus.
In Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications
Security (pp. 2606–2620). Salt Lake City, UT, United States: ACM. https://doi.org/10.1145/3658644.3670286'
chicago: 'Blackshear, Sam, Andrey Chursin, George Danezis, Anastasios Kichidis,
Eleftherios Kokoris Kogias, Xun Li, Mark Logan, et al. “Sui Lutris: A Blockchain
Combining Broadcast and Consensus.” In Proceedings of the 2024 on ACM SIGSAC
Conference on Computer and Communications Security, 2606–20. ACM, 2024. https://doi.org/10.1145/3658644.3670286.'
ieee: 'S. Blackshear et al., “Sui Lutris: A blockchain combining broadcast
and consensus,” in Proceedings of the 2024 on ACM SIGSAC Conference on Computer
and Communications Security, Salt Lake City, UT, United States, 2024, pp.
2606–2620.'
ista: 'Blackshear S, Chursin A, Danezis G, Kichidis A, Kokoris Kogias E, Li X, Logan
M, Menon A, Nowacki T, Sonnino A, Williams B, Zhang L. 2024. Sui Lutris: A blockchain
combining broadcast and consensus. Proceedings of the 2024 on ACM SIGSAC Conference
on Computer and Communications Security. CCS: Conference on Computer and Communications
Security, 2606–2620.'
mla: 'Blackshear, Sam, et al. “Sui Lutris: A Blockchain Combining Broadcast and
Consensus.” Proceedings of the 2024 on ACM SIGSAC Conference on Computer and
Communications Security, ACM, 2024, pp. 2606–20, doi:10.1145/3658644.3670286.'
short: S. Blackshear, A. Chursin, G. Danezis, A. Kichidis, E. Kokoris Kogias, X.
Li, M. Logan, A. Menon, T. Nowacki, A. Sonnino, B. Williams, L. Zhang, in:, Proceedings
of the 2024 on ACM SIGSAC Conference on Computer and Communications Security,
ACM, 2024, pp. 2606–2620.
conference:
end_date: 2024-10-18
location: Salt Lake City, UT, United States
name: 'CCS: Conference on Computer and Communications Security'
start_date: 2024-10-14
date_created: 2025-01-29T12:42:21Z
date_published: 2024-12-09T00:00:00Z
date_updated: 2025-09-09T12:13:55Z
day: '09'
department:
- _id: ElKo
doi: 10.1145/3658644.3670286
external_id:
arxiv:
- '2310.18042'
isi:
- '001436367300178'
fulldoi: https://doi.org/10.1145/3658644.3670286
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2310.18042
month: '12'
oa: 1
oa_version: Preprint
page: 2606-2620
publication: Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications
Security
publication_identifier:
isbn:
- '9798400706363'
publication_status: published
publisher: ACM
quality_controlled: '1'
status: public
title: 'Sui Lutris: A blockchain combining broadcast and consensus'
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18961'
abstract:
- lang: eng
text: "Automated contact tracing (ACT) emerged as a promising measure to curb the
spread of Covid-19. Users enable ACT on their smartphones to automatically record
contacts with other users. If a user tests positive for the disease, they report
their diagnosis to alert their contacts.\r\nDesigning effective ACT protocols
is challenging since they need to be efficient and secure while also ensuring
users' privacy. As ACT protocols necessarily leak some information by design,
defining privacy is difficult. For example, a user cannot deny having met another
user. Ideally, however, the user can plausibly deny everything else, in particular,
when they met. We call this privacy property contact-time deniability.\r\nWhile
some early works discussed contact-time deniability informally, it has received
little attention since then. We investigate deniability from a rigorous, theoretical
point of view and arrive at the following impossibility result:\r\nA decentralized
protocol with unidirectional communication cannot be contact-time deniable and
replay-secure. This holds even if malicious users treat smartphones as black-boxes.\r\n
Unidirectional protocols are usually very efficient and many proposals are unidirectional,
e.g., the widely-deployed Google-Apple Exposure Notifications. So the impossibility
result considerably constrains the design space of efficient, secure, and private
ACT protocols. However, it can also be used as a guide; we discuss several possibilities
to achieve contact-time deniability in practice."
acknowledgement: "We thank Raluca-Georgia Diugan for her initial contributions and
support afterward.\r\nThis research was funded in whole or in part by the Austrian
Science Fund (FWF) 10.55776/F85."
article_processing_charge: No
article_type: original
author:
- first_name: Christoph Ullrich
full_name: Günther, Christoph Ullrich
id: ec98511c-eb8e-11eb-b029-edd25d7271a1
last_name: Günther
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
citation:
ama: 'Günther CU, Pietrzak KZ. Deniability in automated contact tracing: Impossibilities
and possibilities. Proceedings on Privacy Enhancing Technologies. 2024;2024(4):636-648.
doi:10.56553/popets-2024-0134'
apa: 'Günther, C. U., & Pietrzak, K. Z. (2024). Deniability in automated contact
tracing: Impossibilities and possibilities. Proceedings on Privacy Enhancing
Technologies. Bristol, UK/Virtual: Privacy Enhancing Technologies Symposium
Advisory Board. https://doi.org/10.56553/popets-2024-0134'
chicago: 'Günther, Christoph Ullrich, and Krzysztof Z Pietrzak. “Deniability in
Automated Contact Tracing: Impossibilities and Possibilities.” Proceedings
on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium
Advisory Board, 2024. https://doi.org/10.56553/popets-2024-0134.'
ieee: 'C. U. Günther and K. Z. Pietrzak, “Deniability in automated contact tracing:
Impossibilities and possibilities,” Proceedings on Privacy Enhancing Technologies,
vol. 2024, no. 4. Privacy Enhancing Technologies Symposium Advisory Board, pp.
636–648, 2024.'
ista: 'Günther CU, Pietrzak KZ. 2024. Deniability in automated contact tracing:
Impossibilities and possibilities. Proceedings on Privacy Enhancing Technologies.
2024(4), 636–648.'
mla: 'Günther, Christoph Ullrich, and Krzysztof Z. Pietrzak. “Deniability in Automated
Contact Tracing: Impossibilities and Possibilities.” Proceedings on Privacy
Enhancing Technologies, vol. 2024, no. 4, Privacy Enhancing Technologies Symposium
Advisory Board, 2024, pp. 636–48, doi:10.56553/popets-2024-0134.'
short: C.U. Günther, K.Z. Pietrzak, Proceedings on Privacy Enhancing Technologies
2024 (2024) 636–648.
conference:
end_date: 2024-07-20
location: Bristol, UK/Virtual
name: 'PETs: Privacy Enhancing Technologies Symposium '
start_date: 2024-07-15
corr_author: '1'
date_created: 2025-01-29T13:39:34Z
date_published: 2024-07-01T00:00:00Z
date_updated: 2025-04-15T08:16:04Z
day: '01'
ddc:
- '000'
department:
- _id: KrPi
- _id: GradSch
doi: 10.56553/popets-2024-0134
file:
- access_level: open_access
checksum: 348ed6adcf6ad2f925227bde1758cae6
content_type: application/pdf
creator: dernst
date_created: 2025-01-29T13:44:47Z
date_updated: 2025-01-29T13:44:47Z
file_id: '18962'
file_name: 2024_ProcPrivacyEnhTech_Guenther.pdf
file_size: 611567
relation: main_file
success: 1
file_date_updated: 2025-01-29T13:44:47Z
fulldoi: https://doi.org/10.56553/popets-2024-0134
has_accepted_license: '1'
intvolume: ' 2024'
issue: '4'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 636-648
project:
- _id: 34a34d57-11ca-11ed-8bc3-a2688a8724e1
grant_number: F8509
name: Security and Privacy by Design for Complex Systems
publication: Proceedings on Privacy Enhancing Technologies
publication_identifier:
issn:
- 2299-0984
publication_status: published
publisher: Privacy Enhancing Technologies Symposium Advisory Board
quality_controlled: '1'
status: public
title: 'Deniability in automated contact tracing: Impossibilities and possibilities'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2024
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18964'
abstract:
- lang: eng
text: Object-centric learning (OCL) extracts the representation of objects with
slots, offering an exceptional blend of flexibility and interpretability for abstracting
low-level perceptual features. A widely adopted method within OCL is slot attention,
which utilizes attention mechanisms to iteratively refine slot representations.
However, a major draw-back of most object-centric models, including slot attention,
is their reliance on predefining the number of slots. This not only necessitates
prior knowledge of the dataset but also overlooks the inherent variability in
the number of objects present in each instance. To overcome this fundamental limitation,
we present a novel complexity-aware object auto-encoder framework. Within this
framework, we introduce an adaptive slot attention (AdaSlot) mecha-nism that dynamically
determines the optimal number of slots based on the content of the data. This
is achieved by proposing a discrete slot sampling module that is responsible for
selecting an appropriate number of slots from a candidate list. Furthermore, we
introduce a masked slot decoder that suppresses unselected slots during the decoding
process. Our framework, tested extensively on object discovery tasks with various
datasets, shows performance matching or exceeding top fixed-slot models. Moreover,
our analysis substantiates that our method exhibits the capability to dynamically
adapt the slot number according to each instance's complexity, offering the potential
for further exploration in slot attention research. Project will be available
at https://kfan21.github.io/AdaSlot/
acknowledgement: Yanwei Fu is the corresponding authour. Yanwei Fu is with School
of Data Science, Fudan University, Shanghai Key Lab of Intelligent Information Processing,
Fudan University, and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence,
Zhejiang Normal University, Jinhua, China.
article_processing_charge: No
arxiv: 1
author:
- first_name: Ke
full_name: Fan, Ke
last_name: Fan
- first_name: Zechen
full_name: Bai, Zechen
last_name: Bai
- first_name: Tianjun
full_name: Xiao, Tianjun
last_name: Xiao
- first_name: Tong
full_name: He, Tong
last_name: He
- first_name: Max
full_name: Horn, Max
last_name: Horn
- first_name: Yanwei
full_name: Fu, Yanwei
last_name: Fu
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Zheng
full_name: Zhang, Zheng
last_name: Zhang
citation:
ama: 'Fan K, Bai Z, Xiao T, et al. Adaptive slot attention: Object discovery with
dynamic slot number. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern
Recognition. IEEE; 2024. doi:10.1109/cvpr52733.2024.02176'
apa: 'Fan, K., Bai, Z., Xiao, T., He, T., Horn, M., Fu, Y., … Zhang, Z. (2024).
Adaptive slot attention: Object discovery with dynamic slot number. In 2024
IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA,
United States: IEEE. https://doi.org/10.1109/cvpr52733.2024.02176'
chicago: 'Fan, Ke, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco
Locatello, and Zheng Zhang. “Adaptive Slot Attention: Object Discovery with Dynamic
Slot Number.” In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
IEEE, 2024. https://doi.org/10.1109/cvpr52733.2024.02176.'
ieee: 'K. Fan et al., “Adaptive slot attention: Object discovery with dynamic
slot number,” in 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition,
Seattle, WA, United States, 2024.'
ista: 'Fan K, Bai Z, Xiao T, He T, Horn M, Fu Y, Locatello F, Zhang Z. 2024. Adaptive
slot attention: Object discovery with dynamic slot number. 2024 IEEE/CVF Conference
on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision
and Pattern Recognition.'
mla: 'Fan, Ke, et al. “Adaptive Slot Attention: Object Discovery with Dynamic Slot
Number.” 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition,
IEEE, 2024, doi:10.1109/cvpr52733.2024.02176.'
short: K. Fan, Z. Bai, T. Xiao, T. He, M. Horn, Y. Fu, F. Locatello, Z. Zhang, in:,
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2024.
conference:
end_date: 2024-06-22
location: Seattle, WA, United States
name: 'CVPR: Conference on Computer Vision and Pattern Recognition'
start_date: 2024-06-16
date_created: 2025-01-29T14:27:39Z
date_published: 2024-06-15T00:00:00Z
date_updated: 2025-09-09T12:15:17Z
day: '15'
department:
- _id: FrLo
doi: 10.1109/cvpr52733.2024.02176
external_id:
arxiv:
- '2406.09196'
isi:
- '001342515506043'
fulldoi: https://doi.org/10.1109/cvpr52733.2024.02176
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2406.09196
month: '06'
oa: 1
oa_version: Preprint
publication: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition
publication_identifier:
eisbn:
- '9798350353006'
publication_status: published
publisher: IEEE
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://kfan21.github.io/AdaSlot/
status: public
title: 'Adaptive slot attention: Object discovery with dynamic slot number'
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '18967'
abstract:
- lang: eng
text: "Background: We identified small molecule tricyclic pyrone compound CP2 as
a mild mitochondrial complex I (MCI) inhibitor that induces neuroprotection in
multiple mouse models of AD. One of the major concerns while targeting mitochondria
is the production of reactive oxygen species (ROS). CP2 consists of two diastereoisomers,
D1 and D2, with distinct activity and toxicity profiles. This study was designed
to understand how structure of D1 and D2 affects their binding to MCI and the
consequential impact on ROS production.\r\n\r\nMethod: The X-ray crystallography
and cryo-electron microscopy (cryo-EM) at global resolution of 3.25-3.27Å were
employed to identify the molecular structure of D1 and D2 and the D1 binding to
the isolated ovine MCI. The assessment of the MCI inhibition and the extent of
ROS generation were done in isolated MCI and human neuroblastoma MC65 cells using
flow cytometry, a Seahorse extracellular flux analyzer, and the kinetic studies.\r\n\r\nResult:
In the closed conformation of MCI, D1 selectively binds to the deep Quinone-site
(Qd) but not to the shallow Q-site (Qs), sharing the same binding pocket as rotenone.
In the open MCI state, D1 exclusively binds to the Qs in contrast to rotenone,
which binds Qd and Qs in both closed and open states. At the same concentrations,
D1 inhibits respiration to a greater extent compared to D2 (5:1 ratio) and produces
higher level of ROS.\r\n\r\nConclusion:Cryo-EM unambiguously identified binding
of D1 to both the Qd and Qs sites, contingent upon the conformational state of
MCI. In contrast to rotenone, D1 binds Qd only in the closed conformation during
catalytic cycle, leading to mild inhibition. Superimposing X-ray crystallography
data of D1 and D2 onto cryo-EM data suggests that the orientation of the methyl
group in D2 induces a flatter conformation, resulting in lower binding affinity
to MCI, which correlates with lower inhibition and toxicity compared to D1. At
physiologically relevant concentrations, CP2 (D1:D2 = 1:1) demonstrates low MCI
inhibition yielding negligible ROS levels. This observation provides new insight
into the absence of toxicity associated with CP2 treatment in vivo, further highlighting
feasibility for the development of safe and efficacious MCI inhibitors."
article_number: e085971
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Olga
full_name: Petrova, Olga
id: 5D8C9660-5D49-11EA-8188-567B3DDC885E
last_name: Petrova
- first_name: Sergey A
full_name: Trushin, Sergey A
last_name: Trushin
- first_name: Thi Kim Oanh
full_name: Nguyen, Thi Kim Oanh
last_name: Nguyen
- first_name: Mark
full_name: Ostroot, Mark
last_name: Ostroot
- first_name: Matthew
full_name: Schellenberg, Matthew
last_name: Schellenberg
- first_name: Graham
full_name: Johnson, Graham
last_name: Johnson
- first_name: Eugenia
full_name: Trushina, Eugenia
last_name: Trushina
- first_name: Leonid A
full_name: Sazanov, Leonid A
id: 338D39FE-F248-11E8-B48F-1D18A9856A87
last_name: Sazanov
orcid: 0000-0002-0977-7989
citation:
ama: Petrova O, Trushin SA, Nguyen TKO, et al. Structure‐activity Relationship
Study of Neuroprotective Complex I Inhibitor CP2. Vol 20. Wiley; 2024. doi:10.1002/alz.085971
apa: Petrova, O., Trushin, S. A., Nguyen, T. K. O., Ostroot, M., Schellenberg, M.,
Johnson, G., … Sazanov, L. A. (2024). Structure‐activity relationship study
of neuroprotective complex I inhibitor CP2. Alzheimer’s & Dementia
(Vol. 20). Wiley. https://doi.org/10.1002/alz.085971
chicago: Petrova, Olga, Sergey A Trushin, Thi Kim Oanh Nguyen, Mark Ostroot, Matthew
Schellenberg, Graham Johnson, Eugenia Trushina, and Leonid A Sazanov. Structure‐activity
Relationship Study of Neuroprotective Complex I Inhibitor CP2. Alzheimer’s
& Dementia. Vol. 20. Wiley, 2024. https://doi.org/10.1002/alz.085971.
ieee: O. Petrova et al., Structure‐activity relationship study of neuroprotective
complex I inhibitor CP2, vol. 20, no. S6. Wiley, 2024.
ista: Petrova O, Trushin SA, Nguyen TKO, Ostroot M, Schellenberg M, Johnson G, Trushina
E, Sazanov LA. 2024. Structure‐activity relationship study of neuroprotective
complex I inhibitor CP2, Wiley,p.
mla: Petrova, Olga, et al. “Structure‐activity Relationship Study of Neuroprotective
Complex I Inhibitor CP2.” Alzheimer’s & Dementia, vol. 20, no. S6,
e085971, Wiley, 2024, doi:10.1002/alz.085971.
short: O. Petrova, S.A. Trushin, T.K.O. Nguyen, M. Ostroot, M. Schellenberg, G.
Johnson, E. Trushina, L.A. Sazanov, Structure‐activity Relationship Study of Neuroprotective
Complex I Inhibitor CP2, Wiley, 2024.
date_created: 2025-01-29T15:21:40Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2025-01-29T15:29:22Z
day: '01'
ddc:
- '570'
department:
- _id: LeSa
doi: 10.1002/alz.085971
file:
- access_level: open_access
checksum: e914bd5f3a701659ab79d497a122811f
content_type: application/pdf
creator: dernst
date_created: 2025-01-29T15:24:50Z
date_updated: 2025-01-29T15:24:50Z
file_id: '18968'
file_name: 2024_AlzheimerDementia_Petrova.pdf
file_size: 70870
relation: main_file
success: 1
file_date_updated: 2025-01-29T15:24:50Z
fulldoi: https://doi.org/10.1002/alz.085971
has_accepted_license: '1'
intvolume: ' 20'
issue: S6
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: Alzheimer's & Dementia
publication_identifier:
eissn:
- 1552-5279
issn:
- 1552-5260
publication_status: published
publisher: Wiley
quality_controlled: '1'
status: public
title: Structure‐activity relationship study of neuroprotective complex I inhibitor
CP2
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: other_academic_publication
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '18970'
abstract:
- lang: eng
text: Given a smooth projective curve C, nonabelian Hodge theory gives a diffeomorphism
between two different moduli spaces associated to C. The first is the moduli space
of Higgs bundles on C of rank n, which is equipped with the structure of an algebraic
completely integrable Hamiltonian system. The second is the character variety
of representations of the fundamental group of C into GL(n). In 2012, de Cataldo,
Hausel, and Migliorini [1] proposed the P=W conjecture which identifies the perverse
filtration on the cohomology of the Higgs moduli space with the weight filtration
on the cohomology of the character variety. Recently, in 2022, two independent
proofs of the P=W Conjecture appeared, in work of Maulik &Shen [2] and Hausel,
Mellit, Minets &Schiffmann [6]. The aim of the Arbeitsgemeinschaft was to understand
the P=W Conjecture and these two recent proofs.
acknowledgement: "The MFO and the workshop organizers would like to thank the\r\nNational
Science Foundation for supporting the participation of junior researchers\r\nby
the grant DMS-2230648, “US Junior Oberwolfach Fellows”. Moreover, the\r\nMFO and
the workshop organizers would like to thank the Oberwolfach Foundation for supporting
the participation of junior researchers in the Arbeitsgemeinschaft."
article_processing_charge: No
article_type: original
author:
- first_name: Tamás
full_name: Hausel, Tamás
id: 4A0666D8-F248-11E8-B48F-1D18A9856A87
last_name: Hausel
orcid: 0000-0002-9582-2634
- first_name: Davesh
full_name: Maulik, Davesh
last_name: Maulik
- first_name: Anton
full_name: Mellit, Anton
last_name: Mellit
- first_name: Olivier
full_name: Schiffmann, Olivier
last_name: Schiffmann
- first_name: Junliang
full_name: Shen, Junliang
last_name: Shen
citation:
ama: 'Hausel T, Maulik D, Mellit A, Schiffmann O, Shen J. Arbeitsgemeinschaft: Geometry
and representation theory around the P=W conjecture. Oberwolfach Reports.
2024;21(2):949-1004. doi:10.4171/owr/2024/16'
apa: 'Hausel, T., Maulik, D., Mellit, A., Schiffmann, O., & Shen, J. (2024).
Arbeitsgemeinschaft: Geometry and representation theory around the P=W conjecture.
Oberwolfach Reports. EMS Press. https://doi.org/10.4171/owr/2024/16'
chicago: 'Hausel, Tamás, Davesh Maulik, Anton Mellit, Olivier Schiffmann, and Junliang
Shen. “Arbeitsgemeinschaft: Geometry and Representation Theory around the P=W
Conjecture.” Oberwolfach Reports. EMS Press, 2024. https://doi.org/10.4171/owr/2024/16.'
ieee: 'T. Hausel, D. Maulik, A. Mellit, O. Schiffmann, and J. Shen, “Arbeitsgemeinschaft:
Geometry and representation theory around the P=W conjecture,” Oberwolfach
Reports, vol. 21, no. 2. EMS Press, pp. 949–1004, 2024.'
ista: 'Hausel T, Maulik D, Mellit A, Schiffmann O, Shen J. 2024. Arbeitsgemeinschaft:
Geometry and representation theory around the P=W conjecture. Oberwolfach Reports.
21(2), 949–1004.'
mla: 'Hausel, Tamás, et al. “Arbeitsgemeinschaft: Geometry and Representation Theory
around the P=W Conjecture.” Oberwolfach Reports, vol. 21, no. 2, EMS Press,
2024, pp. 949–1004, doi:10.4171/owr/2024/16.'
short: T. Hausel, D. Maulik, A. Mellit, O. Schiffmann, J. Shen, Oberwolfach Reports
21 (2024) 949–1004.
date_created: 2025-01-29T15:34:22Z
date_published: 2024-05-05T00:00:00Z
date_updated: 2025-01-29T15:39:55Z
day: '05'
ddc:
- '500'
department:
- _id: TaHa
doi: 10.4171/owr/2024/16
fulldoi: https://doi.org/10.4171/owr/2024/16
has_accepted_license: '1'
intvolume: ' 21'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.4171/owr/2024/16
month: '05'
oa: 1
oa_version: Published Version
page: 949-1004
publication: Oberwolfach Reports
publication_identifier:
eissn:
- 1660-8941
issn:
- 1660-8933
publication_status: published
publisher: EMS Press
quality_controlled: '1'
status: public
title: 'Arbeitsgemeinschaft: Geometry and representation theory around the P=W conjecture'
tmp:
image: /images/cc_by_sa.png
legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode
name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC
BY-SA 4.0)
short: CC BY-SA (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 21
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18971'
abstract:
- lang: eng
text: 'Models prone to spurious correlations in training data often produce brittle
predictions and introduce unintended biases. Addressing this challenge typically
involves methods relying on prior knowledge and group annotation to remove spurious
correlations, which may not be readily available in many applications. In this
paper, we establish a novel connection between unsupervised object-centric learning
and mitigation of spurious correlations. Instead of directly inferring subgroups
with varying correlations with labels, our approach focuses on discovering concepts:
discrete ideas that are shared across input samples. Leveraging existing object-centric
representation learning, we introduce CoBalT: a concept balancing technique that
effectively mitigates spurious correlations without requiring human labeling of
subgroups. Evaluation across the benchmark datasets for sub-population shifts
demonstrate superior or competitive performance compared state-of-the-art baselines,
without the need for group annotation. Code is available at https://github.com/rarefin/CoBalT'
acknowledgement: "We acknowledge the support of the Canada CIFAR AI Chair Program
and IVADO. We thank Mila and Compute Canada for providing computational resources.\r\n"
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Rifat
full_name: Arefin, Rifat
last_name: Arefin
- first_name: Yan
full_name: Zhang, Yan
last_name: Zhang
- first_name: Aristide
full_name: Baratin, Aristide
last_name: Baratin
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Irina
full_name: Rish, Irina
last_name: Rish
- first_name: Dianbo
full_name: Liu, Dianbo
last_name: Liu
- first_name: Kenji
full_name: Kawaguchi, Kenji
last_name: Kawaguchi
citation:
ama: 'Arefin R, Zhang Y, Baratin A, et al. Unsupervised concept discovery mitigates
spurious correlations. In: Proceedings of the 41st International Conference
on Machine Learning. Vol 235. ML Research Press; 2024:1672-1688.'
apa: 'Arefin, R., Zhang, Y., Baratin, A., Locatello, F., Rish, I., Liu, D., &
Kawaguchi, K. (2024). Unsupervised concept discovery mitigates spurious correlations.
In Proceedings of the 41st International Conference on Machine Learning
(Vol. 235, pp. 1672–1688). Vienna, Austria: ML Research Press.'
chicago: Arefin, Rifat, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina
Rish, Dianbo Liu, and Kenji Kawaguchi. “Unsupervised Concept Discovery Mitigates
Spurious Correlations.” In Proceedings of the 41st International Conference
on Machine Learning, 235:1672–88. ML Research Press, 2024.
ieee: R. Arefin et al., “Unsupervised concept discovery mitigates spurious
correlations,” in Proceedings of the 41st International Conference on Machine
Learning, Vienna, Austria, 2024, vol. 235, pp. 1672–1688.
ista: 'Arefin R, Zhang Y, Baratin A, Locatello F, Rish I, Liu D, Kawaguchi K. 2024.
Unsupervised concept discovery mitigates spurious correlations. Proceedings of
the 41st International Conference on Machine Learning. ICML: International Conference
on Machine Learning, PMLR, vol. 235, 1672–1688.'
mla: Arefin, Rifat, et al. “Unsupervised Concept Discovery Mitigates Spurious Correlations.”
Proceedings of the 41st International Conference on Machine Learning, vol.
235, ML Research Press, 2024, pp. 1672–88.
short: R. Arefin, Y. Zhang, A. Baratin, F. Locatello, I. Rish, D. Liu, K. Kawaguchi,
in:, Proceedings of the 41st International Conference on Machine Learning, ML
Research Press, 2024, pp. 1672–1688.
conference:
end_date: 2024-07-27
location: Vienna, Austria
name: 'ICML: International Conference on Machine Learning'
start_date: 2024-07-21
date_created: 2025-01-30T07:21:57Z
date_published: 2024-07-30T00:00:00Z
date_updated: 2025-01-30T07:23:10Z
day: '30'
department:
- _id: FrLo
external_id:
arxiv:
- '2402.13368'
intvolume: ' 235'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2402.13368
month: '07'
oa: 1
oa_version: Preprint
page: 1672-1688
publication: Proceedings of the 41st International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/rarefin/CoBalT
scopus_import: '1'
status: public
title: Unsupervised concept discovery mitigates spurious correlations
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 235
year: '2024'
...
---
OA_place: publisher
OA_type: green
_id: '18974'
abstract:
- lang: eng
text: Reinforcement Learning (RL) from temporal logical specifications is a fundamental
problem in sequential decision making. One of the basic and core such specification
is the reachability specification that requires a target set to be eventually
visited. Despite strong empirical results for RL from such specifications, the
theoretical guarantees are bleak, including the impossibility of Probably Approximately
Correct (PAC) guarantee for reachability specifications. Given the impossibility
result, in this work we consider the problem of RL from reachability specifications
along with the information of expected conditional distance (ECD). We present
(a) lower bound results which establish the necessity of ECD information for PAC
guarantees and (b) an algorithm that establishes PAC-guarantees given the ECD
information. To the best of our knowledge, this is the first RL from reachability
specifications that does not make any assumptions on the underlying environment
to learn policies.
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Suguman
full_name: Bansal, Suguman
last_name: Bansal
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
citation:
ama: 'Svoboda J, Bansal S, Chatterjee K. Reinforcement learning from reachability
specifications: PAC guarantees with expected conditional distance. In: 41st
International Conference on Machine Learning. Vol 235. ML Research Press;
2024:47331-47344.'
apa: 'Svoboda, J., Bansal, S., & Chatterjee, K. (2024). Reinforcement learning
from reachability specifications: PAC guarantees with expected conditional distance.
In 41st International Conference on Machine Learning (Vol. 235, pp. 47331–47344).
Vienna, Austria: ML Research Press.'
chicago: 'Svoboda, Jakub, Suguman Bansal, and Krishnendu Chatterjee. “Reinforcement
Learning from Reachability Specifications: PAC Guarantees with Expected Conditional
Distance.” In 41st International Conference on Machine Learning, 235:47331–44.
ML Research Press, 2024.'
ieee: 'J. Svoboda, S. Bansal, and K. Chatterjee, “Reinforcement learning from reachability
specifications: PAC guarantees with expected conditional distance,” in 41st
International Conference on Machine Learning, Vienna, Austria, 2024, vol.
235, pp. 47331–47344.'
ista: 'Svoboda J, Bansal S, Chatterjee K. 2024. Reinforcement learning from reachability
specifications: PAC guarantees with expected conditional distance. 41st International
Conference on Machine Learning. ICML: International Conference on Machine Learning,
PMLR, vol. 235, 47331–47344.'
mla: 'Svoboda, Jakub, et al. “Reinforcement Learning from Reachability Specifications:
PAC Guarantees with Expected Conditional Distance.” 41st International Conference
on Machine Learning, vol. 235, ML Research Press, 2024, pp. 47331–44.'
short: J. Svoboda, S. Bansal, K. Chatterjee, in:, 41st International Conference
on Machine Learning, ML Research Press, 2024, pp. 47331–47344.
conference:
end_date: 2024-07-27
location: Vienna, Austria
name: 'ICML: International Conference on Machine Learning'
start_date: 2024-07-21
corr_author: '1'
date_created: 2025-01-30T07:45:22Z
date_published: 2024-07-29T00:00:00Z
date_updated: 2025-01-30T07:46:16Z
day: '29'
department:
- _id: KrCh
intvolume: ' 235'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openreview.net/forum?id=mXUDDL4r1Q
month: '07'
oa: 1
oa_version: Preprint
page: 47331-47344
publication: 41st International Conference on Machine Learning
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Reinforcement learning from reachability specifications: PAC guarantees with
expected conditional distance'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 235
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18975'
abstract:
- lang: eng
text: Leveraging second-order information about the loss at the scale of deep networks
is one of the main lines of approach for improving the performance of current
optimizers for deep learning. Yet, existing approaches for accurate full-matrix
preconditioning, such as Full-Matrix Adagrad (GGT) or Matrix-Free Approximate
Curvature (M-FAC) suffer from massive storage costs when applied even to small-scale
models, as they must store a sliding window of gradients, whose memory requirements
are multiplicative in the model dimension. In this paper, we address this issue
via a novel and efficient error-feedback technique that can be applied to compress
preconditioners by up to two orders of magnitude in practice, without loss of
convergence. Specifically, our approach compresses the gradient information via
sparsification or low-rank compression before it is fed into the preconditioner,
feeding the compression error back into future iterations. Extensive experiments
on deep neural networks show that this approach can compress full-matrix preconditioners
to up to 99% sparsity without accuracy loss, effectively removing the memory overhead
of fullmatrix preconditioners such as GGT and M-FAC.
acknowledged_ssus:
- _id: CampIT
acknowledgement: The authors thank Adrian Vladu, Razvan Pascanu, Alexandra Peste,
Mher Safaryan for their valuable feedback, the IT department from Institute of Science
and Technology Austria for the hardware support and Weights and Biases for the infrastructure
to track all our experiments.
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Ionut-Vlad
full_name: Modoranu, Ionut-Vlad
id: 449f7a18-f128-11eb-9611-9b430c0c6333
last_name: Modoranu
- first_name: Aleksei
full_name: Kalinov, Aleksei
id: 44b7120e-eb97-11eb-a6c2-e1557aa81d02
last_name: Kalinov
orcid: 0000-0003-2189-3904
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Modoranu I-V, Kalinov A, Kurtic E, Frantar E, Alistarh D-A. Error feedback
can accurately compress preconditioners. In: 41st International Conference
on Machine Learning. Vol 235. ML Research Press; 2024:35910-35933.'
apa: 'Modoranu, I.-V., Kalinov, A., Kurtic, E., Frantar, E., & Alistarh, D.-A.
(2024). Error feedback can accurately compress preconditioners. In 41st International
Conference on Machine Learning (Vol. 235, pp. 35910–35933). Vienna, Austria:
ML Research Press.'
chicago: Modoranu, Ionut-Vlad, Aleksei Kalinov, Eldar Kurtic, Elias Frantar, and
Dan-Adrian Alistarh. “Error Feedback Can Accurately Compress Preconditioners.”
In 41st International Conference on Machine Learning, 235:35910–33. ML
Research Press, 2024.
ieee: I.-V. Modoranu, A. Kalinov, E. Kurtic, E. Frantar, and D.-A. Alistarh, “Error
feedback can accurately compress preconditioners,” in 41st International Conference
on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 35910–35933.
ista: 'Modoranu I-V, Kalinov A, Kurtic E, Frantar E, Alistarh D-A. 2024. Error feedback
can accurately compress preconditioners. 41st International Conference on Machine
Learning. ICML: International Conference on Machine Learning, PMLR, vol. 235,
35910–35933.'
mla: Modoranu, Ionut-Vlad, et al. “Error Feedback Can Accurately Compress Preconditioners.”
41st International Conference on Machine Learning, vol. 235, ML Research
Press, 2024, pp. 35910–33.
short: I.-V. Modoranu, A. Kalinov, E. Kurtic, E. Frantar, D.-A. Alistarh, in:, 41st
International Conference on Machine Learning, ML Research Press, 2024, pp. 35910–35933.
conference:
end_date: 2024-07-27
location: Vienna, Austria
name: 'ICML: International Conference on Machine Learning'
start_date: 2024-07-21
corr_author: '1'
date_created: 2025-01-30T07:53:22Z
date_published: 2024-07-30T00:00:00Z
date_updated: 2025-01-30T07:54:16Z
day: '30'
department:
- _id: DaAl
external_id:
arxiv:
- '2306.06098'
intvolume: ' 235'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2306.06098
month: '07'
oa: 1
oa_version: Preprint
page: 35910-35933
publication: 41st International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Error feedback can accurately compress preconditioners
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 235
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18976'
abstract:
- lang: eng
text: We analyze asynchronous-type algorithms for distributed SGD in the heterogeneous
setting, where each worker has its own computation and communication speeds, as
well as data distribution. In these algorithms, workers compute possibly stale
and stochastic gradients associated with their local data at some iteration back
in history and then return those gradients to the server without synchronizing
with other workers. We present a unified convergence theory for non-convex smooth
functions in the heterogeneous regime. The proposed analysis provides convergence
for pure asynchronous SGD and its various modifications. Moreover, our theory
explains what affects the convergence rate and what can be done to improve the
performance of asynchronous algorithms. In particular, we introduce a novel asynchronous
method based on worker shuffling. As a by-product of our analysis, we also demonstrate
convergence guarantees for gradient-type algorithms such as SGD with random reshuffling
and shuffle-once mini-batch SGD. The derived rates match the best-known results
for those algorithms, highlighting the tightness of our approach. Finally, our
numerical evaluations support theoretical findings and show the good practical
performance of our method.
acknowledgement: "The authors thank all anonymous reviewers for their valuable comments
and suggestions on how to improve the manuscript. This work was done when Rustem
Islamov was a Master’s student at Institut Polytechnique de Paris (IP Paris) and
an intern at Institute of Science and Technology Austria (ISTA). The research of
Rustem Islamov was supported by ISTA internship\r\nprogram. Mher Safaryan has received
funding from the European Union’s Horizon 2020 research and innovation program under
the Marie Skłodowska-Curie grant agreement No 101034413."
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Rustem
full_name: Islamov, Rustem
last_name: Islamov
- first_name: Mher
full_name: Safaryan, Mher
id: dd546b39-0804-11ed-9c55-ef075c39778d
last_name: Safaryan
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Islamov R, Safaryan M, Alistarh D-A. AsGrad: A sharp unified analysis of asynchronous-SGD
algorithms. In: Proceedings of The 27th International Conference on Artificial
Intelligence and Statistics. Vol 238. ML Research Press; 2024:649-657.'
apa: 'Islamov, R., Safaryan, M., & Alistarh, D.-A. (2024). AsGrad: A sharp unified
analysis of asynchronous-SGD algorithms. In Proceedings of The 27th International
Conference on Artificial Intelligence and Statistics (Vol. 238, pp. 649–657).
Valencia, Spain: ML Research Press.'
chicago: 'Islamov, Rustem, Mher Safaryan, and Dan-Adrian Alistarh. “AsGrad: A Sharp
Unified Analysis of Asynchronous-SGD Algorithms.” In Proceedings of The 27th
International Conference on Artificial Intelligence and Statistics, 238:649–57.
ML Research Press, 2024.'
ieee: 'R. Islamov, M. Safaryan, and D.-A. Alistarh, “AsGrad: A sharp unified analysis
of asynchronous-SGD algorithms,” in Proceedings of The 27th International Conference
on Artificial Intelligence and Statistics, Valencia, Spain, 2024, vol. 238,
pp. 649–657.'
ista: 'Islamov R, Safaryan M, Alistarh D-A. 2024. AsGrad: A sharp unified analysis
of asynchronous-SGD algorithms. Proceedings of The 27th International Conference
on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence
and Statistics, PMLR, vol. 238, 649–657.'
mla: 'Islamov, Rustem, et al. “AsGrad: A Sharp Unified Analysis of Asynchronous-SGD
Algorithms.” Proceedings of The 27th International Conference on Artificial
Intelligence and Statistics, vol. 238, ML Research Press, 2024, pp. 649–57.'
short: R. Islamov, M. Safaryan, D.-A. Alistarh, in:, Proceedings of The 27th International
Conference on Artificial Intelligence and Statistics, ML Research Press, 2024,
pp. 649–657.
conference:
end_date: 2024-05-04
location: Valencia, Spain
name: 'AISTATS: Conference on Artificial Intelligence and Statistics'
start_date: 2024-05-02
corr_author: '1'
date_created: 2025-01-30T08:15:49Z
date_published: 2024-05-15T00:00:00Z
date_updated: 2025-04-14T07:54:52Z
day: '15'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2310.20452'
intvolume: ' 238'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2310.20452
month: '05'
oa: 1
oa_version: Preprint
page: 649-657
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: Proceedings of The 27th International Conference on Artificial Intelligence
and Statistics
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'AsGrad: A sharp unified analysis of asynchronous-SGD algorithms'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 238
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18977'
abstract:
- lang: eng
text: "Recent advances in large language model (LLM) pretraining have led to high-quality
LLMs with impressive abilities. By compressing such LLMs via quantization to 3-4
bits per parameter, they can fit into memory-limited devices such as laptops and
mobile phones, enabling personalized use. Quantizing models to 3-4 bits per parameter
can lead to moderate to high accuracy losses, especially for smaller models (1-10B
parameters), which are suitable for edge deployment. To address this accuracy
issue, we introduce the Sparse-Quantized Representation (SpQR), a new compressed
format and quantization technique that enables for the first time \\emph{near-lossless}
compression of LLMs across model scales while reaching similar compression levels
to previous methods. SpQR works by identifying and isolating \\emph{outlier weights},
which cause particularly large quantization errors, and storing them in higher
precision while compressing all other weights to 3-4 bits, and achieves relative
accuracy losses of less than \r\n in perplexity for highly-accurate LLaMA and
Falcon LLMs. This makes it possible to run a 33B parameter LLM on a single 24
GB consumer GPU without performance degradation at 15% speedup, thus making powerful
LLMs available to consumers without any downsides. SpQR comes with efficient algorithms
for both encoding weights into its format, as well as decoding them efficiently
at runtime. Specifically, we provide an efficient GPU inference algorithm for
SpQR, which yields faster inference than 16-bit baselines at similar accuracy
while enabling memory compression gains of more than 4x."
acknowledgement: "Denis Kuznedelev acknowledges the support from the Russian Ministry
of Science and Higher\r\nEducation, grant No. 075-10-2021-068. Ruslan Svirschevski
and Vage Egiazarian and Denis\r\nKuznedelev were supported by the grant for research
centers in the field of AI provided by the\r\nAnalytical Center for the Government
of the Russian Federation (ACRF) in accordance with the\r\nagreement on the provision
of subsidies (identifier of the agreement 000000D730321P5Q0002) and the agreement
with HSE University No. 70-2021-00139."
article_processing_charge: No
arxiv: 1
author:
- first_name: Tim
full_name: Dettmers, Tim
last_name: Dettmers
- first_name: Ruslan A.
full_name: Svirschevski, Ruslan A.
last_name: Svirschevski
- first_name: Vage
full_name: Egiazarian, Vage
last_name: Egiazarian
- first_name: Denis
full_name: Kuznedelev, Denis
last_name: Kuznedelev
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Saleh
full_name: Ashkboos, Saleh
last_name: Ashkboos
- first_name: Alexander
full_name: Borzunov, Alexander
last_name: Borzunov
- first_name: Torsten
full_name: Hoefler, Torsten
last_name: Hoefler
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Dettmers T, Svirschevski RA, Egiazarian V, et al. SpQR: A sparse-quantized
representation for near-lossless LLM weight compression. In: 12th International
Conference on Learning Representations. OpenReview; 2024.'
apa: 'Dettmers, T., Svirschevski, R. A., Egiazarian, V., Kuznedelev, D., Frantar,
E., Ashkboos, S., … Alistarh, D.-A. (2024). SpQR: A sparse-quantized representation
for near-lossless LLM weight compression. In 12th International Conference
on Learning Representations. Vienna, Austria: OpenReview.'
chicago: 'Dettmers, Tim, Ruslan A. Svirschevski, Vage Egiazarian, Denis Kuznedelev,
Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, and Dan-Adrian
Alistarh. “SpQR: A Sparse-Quantized Representation for near-Lossless LLM Weight
Compression.” In 12th International Conference on Learning Representations.
OpenReview, 2024.'
ieee: 'T. Dettmers et al., “SpQR: A sparse-quantized representation for near-lossless
LLM weight compression,” in 12th International Conference on Learning Representations,
Vienna, Austria, 2024.'
ista: 'Dettmers T, Svirschevski RA, Egiazarian V, Kuznedelev D, Frantar E, Ashkboos
S, Borzunov A, Hoefler T, Alistarh D-A. 2024. SpQR: A sparse-quantized representation
for near-lossless LLM weight compression. 12th International Conference on Learning
Representations. ICLR: International Conference on Learning Representations.'
mla: 'Dettmers, Tim, et al. “SpQR: A Sparse-Quantized Representation for near-Lossless
LLM Weight Compression.” 12th International Conference on Learning Representations,
OpenReview, 2024.'
short: T. Dettmers, R.A. Svirschevski, V. Egiazarian, D. Kuznedelev, E. Frantar,
S. Ashkboos, A. Borzunov, T. Hoefler, D.-A. Alistarh, in:, 12th International
Conference on Learning Representations, OpenReview, 2024.
conference:
end_date: 2024-05-11
location: Vienna, Austria
name: 'ICLR: International Conference on Learning Representations'
start_date: 2024-05-07
date_created: 2025-01-30T08:26:59Z
date_published: 2024-05-15T00:00:00Z
date_updated: 2025-01-30T08:27:47Z
day: '15'
department:
- _id: DaAl
external_id:
arxiv:
- '2306.03078'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2306.03078
month: '05'
oa: 1
oa_version: Preprint
publication: 12th International Conference on Learning Representations
publication_status: published
publisher: OpenReview
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'SpQR: A sparse-quantized representation for near-lossless LLM weight compression'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
OA_place: repository
_id: '18981'
abstract:
- lang: eng
text: We establish several results combining discrete Morse theory and microlocal
sheaf theory in the setting of finite posets and simplicial complexes. Our primary
tool is a computationally tractable description of the bounded derived category
of sheaves on a poset with the Alexandrov topology. We prove that each bounded
complex of sheaves on a finite poset admits a unique (up to isomorphism of complexes)
minimal injective resolution, and we provide algorithms for computing minimal
injective resolution of an injective complex, as well as several useful functors
between derived categories of sheaves. For the constant sheaf on a simplicial
complex, we give asymptotically tight bounds on the complexity of computing the
minimal injective resolution using those algorithms. Our main result is a novel
definition of the discrete microsupport of a bounded complex of sheaves on a finite
poset. We detail several foundational properties of the discrete microsupport,
as well as a microlocal generalization of the discrete homological Morse theorem
and Morse inequalities.
acknowledgement: "This project has received funding from the European Research Council
(ERC) under the European\r\nUnion’s Horizon 2020 research and innovation programme,
grant no. 788183, from the Wittgenstein Prize,\r\nAustrian Science Fund (FWF), grant
no. Z 342-N31, and from the DFG Collaborative Research Center TRR\r\n109, ‘Discretization
in Geometry and Dynamics’, Austrian Science Fund (FWF), grant no. I 02979-N35."
article_processing_charge: No
arxiv: 1
author:
- first_name: Adam
full_name: Brown, Adam
last_name: Brown
- first_name: Ondrej
full_name: Draganov, Ondrej
id: 2B23F01E-F248-11E8-B48F-1D18A9856A87
last_name: Draganov
orcid: 0000-0003-0464-3823
citation:
ama: Brown A, Draganov O. Discrete microlocal Morse theory. arXiv. doi:10.48550/arXiv.2209.14993
apa: Brown, A., & Draganov, O. (n.d.). Discrete microlocal Morse theory. arXiv.
https://doi.org/10.48550/arXiv.2209.14993
chicago: Brown, Adam, and Ondrej Draganov. “Discrete Microlocal Morse Theory.” ArXiv,
n.d. https://doi.org/10.48550/arXiv.2209.14993.
ieee: A. Brown and O. Draganov, “Discrete microlocal Morse theory,” arXiv.
.
ista: Brown A, Draganov O. Discrete microlocal Morse theory. arXiv, 10.48550/arXiv.2209.14993.
mla: Brown, Adam, and Ondrej Draganov. “Discrete Microlocal Morse Theory.” ArXiv,
doi:10.48550/arXiv.2209.14993.
short: A. Brown, O. Draganov, ArXiv (n.d.).
corr_author: '1'
date_created: 2025-01-31T17:03:04Z
date_published: 2024-06-09T00:00:00Z
date_updated: 2026-04-07T11:47:29Z
day: '09'
department:
- _id: HeEd
doi: 10.48550/arXiv.2209.14993
ec_funded: 1
external_id:
arxiv:
- '2209.14993'
fulldoi: https://doi.org/10.48550/arXiv.2209.14993
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2209.14993
month: '06'
oa: 1
oa_version: Preprint
project:
- _id: 266A2E9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '788183'
name: Alpha Shape Theory Extended
- _id: 268116B8-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00342
name: Mathematics, Computer Science
- _id: 2561EBF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I02979-N35
name: Persistence and stability of geometric complexes
publication: arXiv
publication_status: draft
related_material:
record:
- id: '20323'
relation: later_version
status: public
- id: '18979'
relation: dissertation_contains
status: public
status: public
title: Discrete microlocal Morse theory
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18996'
abstract:
- lang: eng
text: 'We consider the linear causal representation learning setting where we observe
a linear mixing of d unknown latent factors, which follow a linear structural
causal model. Recent work has shown that it is possible to recover the latent
factors as well as the underlying structural causal model over them, up to permutation
and scaling, provided that we have at least d environments, each of which corresponds
to perfect interventions on a single latent node (factor). After this powerful
result, a key open problem faced by the community has been to relax these conditions:
allow for coarser than perfect single-node interventions, and allow for fewer
than d of them, since the number of latent factors d could be very large. In this
work, we consider precisely such a setting, where we allow a smaller than d number
of environments, and also allow for very coarse interventions that can very coarsely
\textit{change the entire causal graph over the latent factors}. On the flip side,
we relax what we wish to extract to simply the \textit{list of nodes that have
shifted between one or more environments}. We provide a surprising identifiability
result that it is indeed possible, under some very mild standard assumptions,
to identify the set of shifted nodes. Our identifiability proof moreover is a
constructive one: we explicitly provide necessary and sufficient conditions for
a node to be a shifted node, and show that we can check these conditions given
observed data. Our algorithm lends itself very naturally to the sample setting
where instead of just interventional distributions, we are provided datasets of
samples from each of these distributions. We corroborate our results on both synthetic
experiments as well as an interesting psychometric dataset. The code can be found
at https://github.com/TianyuCodings/iLCS.'
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Tianyu
full_name: Chen, Tianyu
last_name: Chen
- first_name: Kevin
full_name: Bello, Kevin
last_name: Bello
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Bryon
full_name: Aragam, Bryon
last_name: Aragam
- first_name: Pradeep Kumar
full_name: Ravikumar, Pradeep Kumar
last_name: Ravikumar
citation:
ama: 'Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. Identifying general
mechanism shifts in linear causal representations. In: 38th Conference on Neural
Information Processing Systems. Vol 37. Neural Information Processing Systems
Foundation; 2024.'
apa: 'Chen, T., Bello, K., Locatello, F., Aragam, B., & Ravikumar, P. K. (2024).
Identifying general mechanism shifts in linear causal representations. In 38th
Conference on Neural Information Processing Systems (Vol. 37). Vancouver,
Canada: Neural Information Processing Systems Foundation.'
chicago: Chen, Tianyu, Kevin Bello, Francesco Locatello, Bryon Aragam, and Pradeep
Kumar Ravikumar. “Identifying General Mechanism Shifts in Linear Causal Representations.”
In 38th Conference on Neural Information Processing Systems, Vol. 37. Neural
Information Processing Systems Foundation, 2024.
ieee: T. Chen, K. Bello, F. Locatello, B. Aragam, and P. K. Ravikumar, “Identifying
general mechanism shifts in linear causal representations,” in 38th Conference
on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
ista: 'Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. 2024. Identifying general
mechanism shifts in linear causal representations. 38th Conference on Neural Information
Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in
Neural Information Processing Systems, vol. 37.'
mla: Chen, Tianyu, et al. “Identifying General Mechanism Shifts in Linear Causal
Representations.” 38th Conference on Neural Information Processing Systems,
vol. 37, Neural Information Processing Systems Foundation, 2024.
short: T. Chen, K. Bello, F. Locatello, B. Aragam, P.K. Ravikumar, in:, 38th Conference
on Neural Information Processing Systems, Neural Information Processing Systems
Foundation, 2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
date_created: 2025-02-04T13:09:34Z
date_published: 2024-09-25T00:00:00Z
date_updated: 2025-07-07T13:23:49Z
day: '25'
ddc:
- '000'
department:
- _id: FrLo
external_id:
arxiv:
- '2410.24059'
file:
- access_level: open_access
checksum: 75c3091e70bd2916cd94afbf40a0c425
content_type: application/pdf
creator: dernst
date_created: 2025-02-04T13:09:08Z
date_updated: 2025-02-04T13:09:08Z
file_id: '18997'
file_name: 2024_NeurIPS_Chen.pdf
file_size: 5659119
relation: main_file
success: 1
file_date_updated: 2025-02-04T13:09:08Z
has_accepted_license: '1'
intvolume: ' 37'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: 38th Conference on Neural Information Processing Systems
publication_identifier:
eissn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Identifying general mechanism shifts in linear causal representations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18998'
abstract:
- lang: eng
text: Word embeddings represent language vocabularies as clouds of d-dimensional
points. We investigate how information is conveyed by the general shape of these
clouds, instead of representing the semantic meaning of each token. Specifically,
we use the notion of persistent homology from topological data analysis (TDA)
to measure the distances between language pairs from the shape of their unlabeled
embeddings. These distances quantify the degree of non-isometry of the embeddings.
To distinguish whether these differences are random training errors or capture
real information about the languages, we use the computed distance matrices to
construct language phylogenetic trees over 81 Indo-European languages. Careful
evaluation shows that our reconstructed trees exhibit strong and statistically-significant
similarities to the reference.
article_processing_charge: No
arxiv: 1
author:
- first_name: Ondrej
full_name: Draganov, Ondrej
id: 2B23F01E-F248-11E8-B48F-1D18A9856A87
last_name: Draganov
orcid: 0000-0003-0464-3823
- first_name: Steven
full_name: Skiena, Steven
last_name: Skiena
citation:
ama: 'Draganov O, Skiena S. The shape of word embeddings: Quantifying non-isometry
with topological data analysis. In: Findings of the Association for Computational
Linguistics: EMNLP 2024. Association for Computational Linguistics; 2024:12080-12099.
doi:10.18653/v1/2024.findings-emnlp.705'
apa: 'Draganov, O., & Skiena, S. (2024). The shape of word embeddings: Quantifying
non-isometry with topological data analysis. In Findings of the Association
for Computational Linguistics: EMNLP 2024 (pp. 12080–12099). Miami, FL, United
States: Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.705'
chicago: 'Draganov, Ondrej, and Steven Skiena. “The Shape of Word Embeddings: Quantifying
Non-Isometry with Topological Data Analysis.” In Findings of the Association
for Computational Linguistics: EMNLP 2024, 12080–99. Association for Computational
Linguistics, 2024. https://doi.org/10.18653/v1/2024.findings-emnlp.705.'
ieee: 'O. Draganov and S. Skiena, “The shape of word embeddings: Quantifying non-isometry
with topological data analysis,” in Findings of the Association for Computational
Linguistics: EMNLP 2024, Miami, FL, United States, 2024, pp. 12080–12099.'
ista: 'Draganov O, Skiena S. 2024. The shape of word embeddings: Quantifying non-isometry
with topological data analysis. Findings of the Association for Computational
Linguistics: EMNLP 2024. EMNLP: Conference on Empirical Methods in Natural Language
Processing, 12080–12099.'
mla: 'Draganov, Ondrej, and Steven Skiena. “The Shape of Word Embeddings: Quantifying
Non-Isometry with Topological Data Analysis.” Findings of the Association for
Computational Linguistics: EMNLP 2024, Association for Computational Linguistics,
2024, pp. 12080–99, doi:10.18653/v1/2024.findings-emnlp.705.'
short: 'O. Draganov, S. Skiena, in:, Findings of the Association for Computational
Linguistics: EMNLP 2024, Association for Computational Linguistics, 2024, pp.
12080–12099.'
conference:
end_date: 2024-11-16
location: Miami, FL, United States
name: 'EMNLP: Conference on Empirical Methods in Natural Language Processing'
start_date: 2024-11-12
corr_author: '1'
date_created: 2025-02-04T16:19:28Z
date_published: 2024-11-01T00:00:00Z
date_updated: 2025-02-10T08:21:37Z
day: '01'
ddc:
- '500'
department:
- _id: GradSch
- _id: HeEd
doi: 10.18653/v1/2024.findings-emnlp.705
external_id:
arxiv:
- '2404.00500'
file:
- access_level: open_access
checksum: f4416a5962194f0181ab0dc7f9ef93c0
content_type: application/pdf
creator: dernst
date_created: 2025-02-10T08:20:34Z
date_updated: 2025-02-10T08:20:34Z
file_id: '19016'
file_name: 2024_EMNLP_Draganov.pdf
file_size: 1312638
relation: main_file
success: 1
file_date_updated: 2025-02-10T08:20:34Z
fulldoi: https://doi.org/10.18653/v1/2024.findings-emnlp.705
has_accepted_license: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 12080-12099
publication: 'Findings of the Association for Computational Linguistics: EMNLP 2024'
publication_status: published
publisher: Association for Computational Linguistics
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'The shape of word embeddings: Quantifying non-isometry with topological data
analysis'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18999'
abstract:
- lang: eng
text: Exploring the shape of point configurations has been a key driver in the evolution
of TDA (short for topological data analysis) since its infancy. This survey illustrates
the recent efforts to broaden these ideas to model spatial interactions among
multiple configurations, each distinguished by a color. It describes advances
in this area and prepares the ground for further exploration by mentioning unresolved
questions and promising research avenues while focusing on the overlap with discrete
geometry.
article_number: '2406.04102'
article_processing_charge: No
arxiv: 1
author:
- first_name: Sebastiano
full_name: Cultrera di Montesano, Sebastiano
id: 34D2A09C-F248-11E8-B48F-1D18A9856A87
last_name: Cultrera di Montesano
orcid: 0000-0001-6249-0832
- first_name: Ondrej
full_name: Draganov, Ondrej
id: 2B23F01E-F248-11E8-B48F-1D18A9856A87
last_name: Draganov
orcid: 0000-0003-0464-3823
- first_name: Herbert
full_name: Edelsbrunner, Herbert
id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
last_name: Edelsbrunner
orcid: 0000-0002-9823-6833
- first_name: Morteza
full_name: Saghafian, Morteza
id: f86f7148-b140-11ec-9577-95435b8df824
last_name: Saghafian
citation:
ama: Cultrera di Montesano S, Draganov O, Edelsbrunner H, Saghafian M. Chromatic
topological data analysis. arXiv. doi:10.48550/ARXIV.2406.04102
apa: Cultrera di Montesano, S., Draganov, O., Edelsbrunner, H., & Saghafian,
M. (n.d.). Chromatic topological data analysis. arXiv. https://doi.org/10.48550/ARXIV.2406.04102
chicago: Cultrera di Montesano, Sebastiano, Ondrej Draganov, Herbert Edelsbrunner,
and Morteza Saghafian. “Chromatic Topological Data Analysis.” ArXiv, n.d.
https://doi.org/10.48550/ARXIV.2406.04102.
ieee: S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, and M. Saghafian,
“Chromatic topological data analysis,” arXiv. .
ista: Cultrera di Montesano S, Draganov O, Edelsbrunner H, Saghafian M. Chromatic
topological data analysis. arXiv, 2406.04102.
mla: Cultrera di Montesano, Sebastiano, et al. “Chromatic Topological Data Analysis.”
ArXiv, 2406.04102, doi:10.48550/ARXIV.2406.04102.
short: S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, M. Saghafian, ArXiv
(n.d.).
corr_author: '1'
date_created: 2025-02-04T16:21:21Z
date_published: 2024-06-06T00:00:00Z
date_updated: 2025-02-10T08:14:27Z
day: '06'
ddc:
- '510'
department:
- _id: GradSch
- _id: HeEd
doi: 10.48550/ARXIV.2406.04102
external_id:
arxiv:
- '2406.04102'
fulldoi: https://doi.org/10.48550/ARXIV.2406.04102
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2406.04102
month: '06'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Chromatic topological data analysis
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...