---
OA_place: publisher
OA_type: hybrid
_id: '22564'
abstract:
- lang: eng
text: "It is well known that cities increase air and surface temperatures compared
to their rural surroundings, the so-called urban heat island (UHI) effect. However,
the associated changes in atmospheric humidity (also known as urban dry island,
UDI) and convection triggering remain largely unexplored and it is still unclear
how urban modifications of the surface energy budget Influence the diurnal evolution
of temperature and humidity in the Atmospheric Boundary Layer\r\n(ABL) and ultimately
control the initiation of convective clouds.\r\nHere we quantify the impact of
different urban settings and free atmospheric conditions on\r\nUHI, UDI, and convection
triggers by means of a zero-order model of the ABL. Specifically, we\r\nderive
an approximate solution for urban-rural changes in surface energy fluxes and ABL
potential\r\ntemperature and humidity and we investigate the crossing between
the ABL height and the lifting\r\ncondensation level (LCL) which is a proxy for
the triggering of convective clouds. We show that\r\nurban areas are generally
warmer and drier, thus causing an increase in both ABL and LCL\r\nheights. However,
the response of the ABL-LCL crossing to surface conditions is non-linear and\r\nthere
exists a range of free atmosphere conditions for which changes in imperviousness
can\r\nimpact convective clouds."
article_number: '101346'
article_processing_charge: No
article_type: original
author:
- first_name: Clinton T.F.
full_name: Chiu, Clinton T.F.
last_name: Chiu
- first_name: Kai
full_name: Wang, Kai
last_name: Wang
- first_name: Athanasios
full_name: Paschalis, Athanasios
last_name: Paschalis
- first_name: Tohid
full_name: Erfani, Tohid
last_name: Erfani
- first_name: Nadav
full_name: Peleg, Nadav
last_name: Peleg
- first_name: Simone
full_name: Fatichi, Simone
id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
last_name: Fatichi
- first_name: Natalie
full_name: Theeuwes, Natalie
last_name: Theeuwes
- first_name: Gabriele
full_name: Manoli, Gabriele
last_name: Manoli
citation:
ama: Chiu CTF, Wang K, Paschalis A, et al. An analytical approximation of urban
heat and dry islands and their impact on convection triggering. Urban Climate.
2022;46. doi:10.1016/j.uclim.2022.101346
apa: Chiu, C. T. F., Wang, K., Paschalis, A., Erfani, T., Peleg, N., Fatichi, S.,
… Manoli, G. (2022). An analytical approximation of urban heat and dry islands
and their impact on convection triggering. Urban Climate. Elsevier. https://doi.org/10.1016/j.uclim.2022.101346
chicago: Chiu, Clinton T.F., Kai Wang, Athanasios Paschalis, Tohid Erfani, Nadav
Peleg, Simone Fatichi, Natalie Theeuwes, and Gabriele Manoli. “An Analytical Approximation
of Urban Heat and Dry Islands and Their Impact on Convection Triggering.” Urban
Climate. Elsevier, 2022. https://doi.org/10.1016/j.uclim.2022.101346.
ieee: C. T. F. Chiu et al., “An analytical approximation of urban heat and
dry islands and their impact on convection triggering,” Urban Climate,
vol. 46. Elsevier, 2022.
ista: Chiu CTF, Wang K, Paschalis A, Erfani T, Peleg N, Fatichi S, Theeuwes N, Manoli
G. 2022. An analytical approximation of urban heat and dry islands and their impact
on convection triggering. Urban Climate. 46, 101346.
mla: Chiu, Clinton T. F., et al. “An Analytical Approximation of Urban Heat and
Dry Islands and Their Impact on Convection Triggering.” Urban Climate,
vol. 46, 101346, Elsevier, 2022, doi:10.1016/j.uclim.2022.101346.
short: C.T.F. Chiu, K. Wang, A. Paschalis, T. Erfani, N. Peleg, S. Fatichi, N. Theeuwes,
G. Manoli, Urban Climate 46 (2022).
das_tickbox: '1'
date_created: 2026-07-27T12:30:24Z
date_published: 2022-12-01T00:00:00Z
date_updated: 2026-08-06T14:03:31Z
day: '01'
doi: 10.1016/j.uclim.2022.101346
extern: '1'
intvolume: ' 46'
keyword:
- Urban heat island
- Urban dry island
- Boundary layer
- Convective clouds
- Analytical model
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
main_file_link:
- open_access: '1'
url: https://doi.org/10.1016/j.uclim.2022.101346
month: '12'
oa: 1
oa_version: Published Version
publication: Urban Climate
publication_identifier:
eissn:
- 2212-0955
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: An analytical approximation of urban heat and dry islands and their impact
on convection triggering
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: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 46
year: '2022'
...
---
_id: '10827'
abstract:
- lang: eng
text: Titanium dioxide has been extensively studied in the rutile or anatase phase,
while its high-pressure phases are less well-understood, despite that many are
thought to have interesting optical, mechanical, and electrochemical properties.
First-principles methods, such as density functional theory (DFT), are often used
to compute the enthalpies of TiO2 phases at 0 K, but they are expensive and, thus,
impractical for long time scale and large system-size simulations at finite temperatures.
On the other hand, cheap empirical potentials fail to capture the relative stabilities
of various polymorphs. To model the thermodynamic behaviors of ambient and high-pressure
phases of TiO2, we design an empirical model as a baseline and then train a machine
learning potential based on the difference between the DFT data and the empirical
model. This so-called Δ-learning potential contains long-range electrostatic interactions
and predicts the 0 K enthalpies of stable TiO2 phases that are in good agreement
with DFT. We construct a pressure–temperature phase diagram of TiO2 in the range
0 < P < 70 GPa and 100 < T < 1500 K. We then simulate dynamic phase transition
processes by compressing anatase at different temperatures. At 300 K, we predominantly
observe an anatase-to-baddeleyite transformation at about 20 GPa via a martensitic
two-step mechanism with a highly ordered and collective atomic motion. At 2000
K, anatase can transform into cotunnite around 45–55 GPa in a thermally activated
and probabilistic manner, accompanied by diffusive movement of oxygen atoms. The
pressures computed for these transitions show good agreement with experiments.
Our results shed light on how to synthesize and stabilize high-pressure TiO2 phases,
and our method is generally applicable to other functional materials with multiple
polymorphs.
acknowledgement: J.G.L. and B.C. acknowledge the resources provided by the Cambridge
Tier-2 system operated by the University of Cambridge Research Computing Service
funded by the EPSRC Tier-2 capital (Grant No. EP/P020259/1).
article_number: '074106'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Jacob G.
full_name: Lee, Jacob G.
last_name: Lee
- first_name: Chris J.
full_name: Pickard, Chris J.
last_name: Pickard
- first_name: Bingqing
full_name: Cheng, Bingqing
id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
last_name: Cheng
orcid: 0000-0002-3584-9632
citation:
ama: Lee JG, Pickard CJ, Cheng B. High-pressure phase behaviors of titanium dioxide
revealed by a Δ-learning potential. The Journal of chemical physics. 2022;156(7).
doi:10.1063/5.0079844
apa: Lee, J. G., Pickard, C. J., & Cheng, B. (2022). High-pressure phase behaviors
of titanium dioxide revealed by a Δ-learning potential. The Journal of Chemical
Physics. AIP Publishing. https://doi.org/10.1063/5.0079844
chicago: Lee, Jacob G., Chris J. Pickard, and Bingqing Cheng. “High-Pressure Phase
Behaviors of Titanium Dioxide Revealed by a Δ-Learning Potential.” The Journal
of Chemical Physics. AIP Publishing, 2022. https://doi.org/10.1063/5.0079844.
ieee: J. G. Lee, C. J. Pickard, and B. Cheng, “High-pressure phase behaviors of
titanium dioxide revealed by a Δ-learning potential,” The Journal of chemical
physics, vol. 156, no. 7. AIP Publishing, 2022.
ista: Lee JG, Pickard CJ, Cheng B. 2022. High-pressure phase behaviors of titanium
dioxide revealed by a Δ-learning potential. The Journal of chemical physics. 156(7),
074106.
mla: Lee, Jacob G., et al. “High-Pressure Phase Behaviors of Titanium Dioxide Revealed
by a Δ-Learning Potential.” The Journal of Chemical Physics, vol. 156,
no. 7, 074106, AIP Publishing, 2022, doi:10.1063/5.0079844.
short: J.G. Lee, C.J. Pickard, B. Cheng, The Journal of Chemical Physics 156 (2022).
corr_author: '1'
das_tickbox: '1'
dataavailabilitystatement: All original data generated for the study and the Δ-learning
potential for TiO2 constructed in this study are in the SI repository at https://github.com/jacobglee1/tio2-mlp.
date_created: 2022-03-06T23:01:53Z
date_published: 2022-02-16T00:00:00Z
date_updated: 2026-08-07T11:17:03Z
day: '16'
department:
- _id: BiCh
doi: 10.1063/5.0079844
external_id:
arxiv:
- '2111.12968'
isi:
- '000796704500014'
pmid:
- '35183078'
intvolume: ' 156'
isi: 1
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2111.12968
month: '02'
oa: 1
oa_version: Preprint
pmid: 1
publication: The Journal of chemical physics
publication_identifier:
eissn:
- 1089-7690
publication_status: published
publisher: AIP Publishing
quality_controlled: '1'
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: yes
title: High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning
potential
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 156
year: '2022'
...
---
_id: '12128'
abstract:
- lang: eng
text: We introduce a machine-learning (ML) framework for high-throughput benchmarking
of diverse representations of chemical systems against datasets of materials and
molecules. The guiding principle underlying the benchmarking approach is to evaluate
raw descriptor performance by limiting model complexity to simple regression schemes
while enforcing best ML practices, allowing for unbiased hyperparameter optimization,
and assessing learning progress through learning curves along series of synchronized
train-test splits. The resulting models are intended as baselines that can inform
future method development, in addition to indicating how easily a given dataset
can be learnt. Through a comparative analysis of the training outcome across a
diverse set of physicochemical, topological and geometric representations, we
glean insight into the relative merits of these representations as well as their
interrelatedness.
acknowledgement: 'C P acknowledges funding from Astex through the Sustaining Innovation
Program under the Milner Consortium. B C acknowledges resources provided by the
Cambridge Tier-2 system operated by the University of Cambridge Research Computing
Service funded by EPSRC Tier-2 capital Grant EP/P020259/1. F A F acknowledges funding
from the Swiss National Science Foundation (Grant No. P2BSP2_191736). '
article_number: '040501'
article_processing_charge: No
article_type: original
author:
- first_name: Carl
full_name: Poelking, Carl
last_name: Poelking
- first_name: Felix A
full_name: Faber, Felix A
last_name: Faber
- first_name: Bingqing
full_name: Cheng, Bingqing
id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
last_name: Cheng
orcid: 0000-0002-3584-9632
citation:
ama: 'Poelking C, Faber FA, Cheng B. BenchML: An extensible pipelining framework
for benchmarking representations of materials and molecules at scale. Machine
Learning: Science and Technology. 2022;3(4). doi:10.1088/2632-2153/ac4d11'
apa: 'Poelking, C., Faber, F. A., & Cheng, B. (2022). BenchML: An extensible
pipelining framework for benchmarking representations of materials and molecules
at scale. Machine Learning: Science and Technology. IOP Publishing. https://doi.org/10.1088/2632-2153/ac4d11'
chicago: 'Poelking, Carl, Felix A Faber, and Bingqing Cheng. “BenchML: An Extensible
Pipelining Framework for Benchmarking Representations of Materials and Molecules
at Scale.” Machine Learning: Science and Technology. IOP Publishing, 2022.
https://doi.org/10.1088/2632-2153/ac4d11.'
ieee: 'C. Poelking, F. A. Faber, and B. Cheng, “BenchML: An extensible pipelining
framework for benchmarking representations of materials and molecules at scale,”
Machine Learning: Science and Technology, vol. 3, no. 4. IOP Publishing,
2022.'
ista: 'Poelking C, Faber FA, Cheng B. 2022. BenchML: An extensible pipelining framework
for benchmarking representations of materials and molecules at scale. Machine
Learning: Science and Technology. 3(4), 040501.'
mla: 'Poelking, Carl, et al. “BenchML: An Extensible Pipelining Framework for Benchmarking
Representations of Materials and Molecules at Scale.” Machine Learning: Science
and Technology, vol. 3, no. 4, 040501, IOP Publishing, 2022, doi:10.1088/2632-2153/ac4d11.'
short: 'C. Poelking, F.A. Faber, B. Cheng, Machine Learning: Science and Technology
3 (2022).'
corr_author: '1'
das_tickbox: '1'
dataavailabilitystatement: The datasets used for this study are available at https://github.com/BingqingCheng/linear-regression-benchmarks.
All data that support the findings of this study are included within the article
(and any supplementary files).
date_created: 2023-01-12T12:02:21Z
date_published: 2022-11-17T00:00:00Z
date_updated: 2026-08-07T11:19:31Z
day: '17'
ddc:
- '000'
department:
- _id: BiCh
doi: 10.1088/2632-2153/ac4d11
external_id:
isi:
- '000886534000001'
file:
- access_level: open_access
checksum: 8930d4ad6ed9b47358c6f1a68666adb6
content_type: application/pdf
creator: dernst
date_created: 2023-01-23T10:42:04Z
date_updated: 2023-01-23T10:42:04Z
file_id: '12343'
file_name: 2022_MachLearning_Poelking.pdf
file_size: 13814559
relation: main_file
success: 1
file_date_updated: 2023-01-23T10:42:04Z
has_accepted_license: '1'
intvolume: ' 3'
isi: 1
issue: '4'
keyword:
- Artificial Intelligence
- Human-Computer Interaction
- Software
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
publication: 'Machine Learning: Science and Technology'
publication_identifier:
issn:
- 2632-2153
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/capoe/benchml
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: yes
title: 'BenchML: An extensible pipelining framework for benchmarking representations
of materials and molecules at scale'
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 3
year: '2022'
...
---
_id: '12249'
abstract:
- lang: eng
text: 'The chemical potential of a component in a solution is defined as the free
energy change as the amount of that component changes. Computing this fundamental
thermodynamic property from atomistic simulations is notoriously difficult because
of the convergence issues involved in free energy methods and finite size effects.
This Communication presents the so-called S0 method, which can be used to obtain
chemical potentials from static structure factors computed from equilibrium molecular
dynamics simulations under the isothermal–isobaric ensemble. This new method is
demonstrated on the systems of binary Lennard-Jones particles, urea–water mixtures,
a NaCl aqueous solution, and a high-pressure carbon–hydrogen mixture. '
acknowledgement: I thank Daan Frenkel for providing feedback on an early draft and
for stimulating discussions, Debashish Mukherji and Robinson Cortes-Huerto for sharing
the trajectories for urea–water mixtures, and Aleks Reinhardt for useful suggestions
on the manuscript.
article_number: '121101'
article_processing_charge: No
article_type: original
author:
- first_name: Bingqing
full_name: Cheng, Bingqing
id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
last_name: Cheng
orcid: 0000-0002-3584-9632
citation:
ama: Cheng B. Computing chemical potentials of solutions from structure factors.
The Journal of Chemical Physics. 2022;157(12). doi:10.1063/5.0107059
apa: Cheng, B. (2022). Computing chemical potentials of solutions from structure
factors. The Journal of Chemical Physics. AIP Publishing. https://doi.org/10.1063/5.0107059
chicago: Cheng, Bingqing. “Computing Chemical Potentials of Solutions from Structure
Factors.” The Journal of Chemical Physics. AIP Publishing, 2022. https://doi.org/10.1063/5.0107059.
ieee: B. Cheng, “Computing chemical potentials of solutions from structure factors,”
The Journal of Chemical Physics, vol. 157, no. 12. AIP Publishing, 2022.
ista: Cheng B. 2022. Computing chemical potentials of solutions from structure factors.
The Journal of Chemical Physics. 157(12), 121101.
mla: Cheng, Bingqing. “Computing Chemical Potentials of Solutions from Structure
Factors.” The Journal of Chemical Physics, vol. 157, no. 12, 121101, AIP
Publishing, 2022, doi:10.1063/5.0107059.
short: B. Cheng, The Journal of Chemical Physics 157 (2022).
corr_author: '1'
das_tickbox: '1'
dataavailabilitystatement: "All PYTHON scripts and simulation input files generated
for the study are in the SI repository https://github.com/BingqingCheng/S0, Ref.
29.\r\n29. B. Cheng, https://github.com/BingqingCheng/S0 “Data repository for the
S0 method” (2020)."
date_created: 2023-01-16T09:56:20Z
date_published: 2022-09-30T00:00:00Z
date_updated: 2026-08-07T11:22:29Z
day: '30'
ddc:
- '530'
- '540'
department:
- _id: BiCh
doi: 10.1063/5.0107059
external_id:
isi:
- '000862856000003'
pmid:
- '36182422'
file:
- access_level: open_access
checksum: b0915b706568a663a9a372fca24adf35
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T09:07:00Z
date_updated: 2023-01-30T09:07:00Z
file_id: '12441'
file_name: 2022_JourChemPhysics_Cheng.pdf
file_size: 4402384
relation: main_file
success: 1
file_date_updated: 2023-01-30T09:07:00Z
has_accepted_license: '1'
intvolume: ' 157'
isi: 1
issue: '12'
keyword:
- Physical and Theoretical Chemistry
- General Physics and Astronomy
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
pmid: 1
publication: The Journal of Chemical Physics
publication_identifier:
eissn:
- 1089-7690
issn:
- 0021-9606
publication_status: published
publisher: AIP Publishing
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/ BingqingCheng/S0
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: yes
title: Computing chemical potentials of solutions from structure factors
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 157
year: '2022'
...
---
_id: '11937'
abstract:
- lang: eng
text: Most experimentally known high-pressure ice phases have a body-centred cubic
(bcc) oxygen lattice. Our large-scale molecular-dynamics simulations with a machine-learning
potential indicate that, amongst these bcc ice phases, ices VII, VII′ and X are
the same thermodynamic phase under different conditions, whereas superionic ice
VII″ has a first-order phase boundary with ice VII′. Moreover, at about 300 GPa,
the transformation between ice X and the Pbcm phase has a sharp structural change
but no apparent activation barrier, whilst at higher pressures the barrier gradually
increases. Our study thus clarifies the phase behaviour of the high-pressure ices
and reveals peculiar solid–solid transition mechanisms not known in other systems.
acknowledgement: We thank Chris Pickard for providing the initial structures of high-pressure
ice phases and for useful advice. A.R. and B.C. acknowledge resources provided by
the Cambridge Tier-2 system operated by the University of Cambridge Research Computing
Service funded by EPSRC Tier-2 capital grant EP/P020259/1. M.B. was supported by
the European Union within the Marie Skłodowska-Curie actions (xICE grant 894725)
and acknowledges computational resources at North-German Supercomputing Alliance
(HLRN) facilities. S.H. and M.M. acknowledge support from LDRD 19-ERD-031 and computing
support from the Lawrence Livermore National Laboratory (LLNL) Institutional Computing
Grand Challenge programme. F.C. acknowledges support from the US DOE Office of Science,
Office of Fusion Energy Sciences. Lawrence Livermore National Laboratory is operated
by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy,
National Nuclear Security Administration under Contract DE-AC52-07NA27344.
article_number: '4707'
article_processing_charge: No
article_type: original
author:
- first_name: Aleks
full_name: Reinhardt, Aleks
last_name: Reinhardt
- first_name: Mandy
full_name: Bethkenhagen, Mandy
last_name: Bethkenhagen
- first_name: Federica
full_name: Coppari, Federica
last_name: Coppari
- first_name: Marius
full_name: Millot, Marius
last_name: Millot
- first_name: Sebastien
full_name: Hamel, Sebastien
last_name: Hamel
- first_name: Bingqing
full_name: Cheng, Bingqing
id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
last_name: Cheng
orcid: 0000-0002-3584-9632
citation:
ama: Reinhardt A, Bethkenhagen M, Coppari F, Millot M, Hamel S, Cheng B. Thermodynamics
of high-pressure ice phases explored with atomistic simulations. Nature Communications.
2022;13. doi:10.1038/s41467-022-32374-1
apa: Reinhardt, A., Bethkenhagen, M., Coppari, F., Millot, M., Hamel, S., &
Cheng, B. (2022). Thermodynamics of high-pressure ice phases explored with atomistic
simulations. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-022-32374-1
chicago: Reinhardt, Aleks, Mandy Bethkenhagen, Federica Coppari, Marius Millot,
Sebastien Hamel, and Bingqing Cheng. “Thermodynamics of High-Pressure Ice Phases
Explored with Atomistic Simulations.” Nature Communications. Springer Nature,
2022. https://doi.org/10.1038/s41467-022-32374-1.
ieee: A. Reinhardt, M. Bethkenhagen, F. Coppari, M. Millot, S. Hamel, and B. Cheng,
“Thermodynamics of high-pressure ice phases explored with atomistic simulations,”
Nature Communications, vol. 13. Springer Nature, 2022.
ista: Reinhardt A, Bethkenhagen M, Coppari F, Millot M, Hamel S, Cheng B. 2022.
Thermodynamics of high-pressure ice phases explored with atomistic simulations.
Nature Communications. 13, 4707.
mla: Reinhardt, Aleks, et al. “Thermodynamics of High-Pressure Ice Phases Explored
with Atomistic Simulations.” Nature Communications, vol. 13, 4707, Springer
Nature, 2022, doi:10.1038/s41467-022-32374-1.
short: A. Reinhardt, M. Bethkenhagen, F. Coppari, M. Millot, S. Hamel, B. Cheng,
Nature Communications 13 (2022).
corr_author: '1'
das_tickbox: '1'
dataavailabilitystatement: All original data generated for the study are in the SI
repository https://github.com/BingqingCheng/highP-ice.
date_created: 2022-08-21T22:01:55Z
date_published: 2022-08-10T00:00:00Z
date_updated: 2026-08-07T11:18:25Z
day: '10'
ddc:
- '540'
department:
- _id: BiCh
doi: 10.1038/s41467-022-32374-1
external_id:
isi:
- '000838655300022'
pmid:
- '35948550'
file:
- access_level: open_access
checksum: 8ff9b689cde59fd3a9959a9f01929dea
content_type: application/pdf
creator: dernst
date_created: 2022-08-22T06:33:02Z
date_updated: 2022-08-22T06:33:02Z
file_id: '11939'
file_name: 2022_NatureCommunications_Reinhardt.pdf
file_size: 1767206
relation: main_file
success: 1
file_date_updated: 2022-08-22T06:33:02Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
pmid: 1
publication: Nature Communications
publication_identifier:
eissn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: yes
title: Thermodynamics of high-pressure ice phases explored with atomistic simulations
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 13
year: '2022'
...
---
_id: '9695'
abstract:
- lang: eng
text: Real-world data typically contain a large number of features that are often
heterogeneous in nature, relevance, and also units of measure. When assessing
the similarity between data points, one can build various distance measures using
subsets of these features. Using the fewest features but still retaining sufficient
information about the system is crucial in many statistical learning approaches,
particularly when data are sparse. We introduce a statistical test that can assess
the relative information retained when using two different distance measures,
and determine if they are equivalent, independent, or if one is more informative
than the other. This in turn allows finding the most informative distance measure
out of a pool of candidates. The approach is applied to find the most relevant
policy variables for controlling the Covid-19 epidemic and to find compact yet
informative representations of atomic structures, but its potential applications
are wide ranging in many branches of science.
acknowledgement: "A.G., C.Z., and A.L. gratefully acknowledge support from the European
Union’s Horizon 2020 research and innovation program (grant number 824143, MaX ’Materials
design at the eXascale’ Centre of Excellence). The authors would like to thank M.
Carli, D. Doimo, and I. Macocco (SISSA) for the discussions, M. Caro (Aalto University)
for the precious help in using the TurboGap code, and D. Frenkel (University of
Cambridge) and N. Bernstein (US Naval Research Laboratory) for useful feedback on
the manuscript.\r\nThis work is supported in part by funds from the European Union’s
Horizon 2020 research and innovation program (grant number 824143, MaX ’Materials
design at the eXascale’ Centre of Excellence)."
article_number: pgac039
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Aldo
full_name: Glielmo, Aldo
last_name: Glielmo
- first_name: Claudio
full_name: Zeni, Claudio
last_name: Zeni
- first_name: Bingqing
full_name: Cheng, Bingqing
id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
last_name: Cheng
orcid: 0000-0002-3584-9632
- first_name: Gabor
full_name: Csanyi, Gabor
last_name: Csanyi
- first_name: Alessandro
full_name: Laio, Alessandro
last_name: Laio
citation:
ama: Glielmo A, Zeni C, Cheng B, Csanyi G, Laio A. Ranking the information content
of distance measures. PNAS Nexus. 2022;1(2). doi:10.1093/pnasnexus/pgac039
apa: Glielmo, A., Zeni, C., Cheng, B., Csanyi, G., & Laio, A. (2022). Ranking
the information content of distance measures. PNAS Nexus. Oxford University
Press. https://doi.org/10.1093/pnasnexus/pgac039
chicago: Glielmo, Aldo, Claudio Zeni, Bingqing Cheng, Gabor Csanyi, and Alessandro
Laio. “Ranking the Information Content of Distance Measures.” PNAS Nexus.
Oxford University Press, 2022. https://doi.org/10.1093/pnasnexus/pgac039.
ieee: A. Glielmo, C. Zeni, B. Cheng, G. Csanyi, and A. Laio, “Ranking the information
content of distance measures,” PNAS Nexus, vol. 1, no. 2. Oxford University
Press, 2022.
ista: Glielmo A, Zeni C, Cheng B, Csanyi G, Laio A. 2022. Ranking the information
content of distance measures. PNAS Nexus. 1(2), pgac039.
mla: Glielmo, Aldo, et al. “Ranking the Information Content of Distance Measures.”
PNAS Nexus, vol. 1, no. 2, pgac039, Oxford University Press, 2022, doi:10.1093/pnasnexus/pgac039.
short: A. Glielmo, C. Zeni, B. Cheng, G. Csanyi, A. Laio, PNAS Nexus 1 (2022).
das_tickbox: '1'
dataavailabilitystatement: Details on the datasets used are available in the supplementary
material.
date_created: 2021-07-20T06:31:53Z
date_published: 2022-05-01T00:00:00Z
date_updated: 2026-08-07T11:23:54Z
day: '01'
ddc:
- '000'
department:
- _id: BiCh
doi: 10.1093/pnasnexus/pgac039
external_id:
arxiv:
- '2104.15079'
pmid:
- '36713323'
file:
- access_level: open_access
checksum: f6552854d760eb574ce97abce2c8ef89
content_type: application/pdf
creator: dernst
date_created: 2024-05-29T06:21:33Z
date_updated: 2024-05-29T06:21:33Z
file_id: '17080'
file_name: 2022_PNASNexus_Glielmo.pdf
file_size: 2005167
relation: main_file
success: 1
file_date_updated: 2024-05-29T06:21:33Z
has_accepted_license: '1'
intvolume: ' 1'
issue: '2'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
pmid: 1
publication: PNAS Nexus
publication_identifier:
eissn:
- 2752-6542
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: yes
title: Ranking the information content of distance measures
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 1
year: '2022'
...
---
_id: '12237'
abstract:
- lang: eng
text: Thermoelectric technology requires synthesizing complex materials where not
only the crystal structure but also other structural features such as defects,
grain size and orientation, and interfaces must be controlled. To date, conventional
solid-state techniques are unable to provide this level of control. Herein, we
present a synthetic approach in which dense inorganic thermoelectric materials
are produced by the consolidation of well-defined nanoparticle powders. The idea
is that controlling the characteristics of the powder allows the chemical transformations
that take place during consolidation to be guided, ultimately yielding inorganic
solids with targeted features. Different from conventional methods, syntheses
in solution can produce particles with unprecedented control over their size,
shape, crystal structure, composition, and surface chemistry. However, to date,
most works have focused only on the low-cost benefits of this strategy. In this
perspective, we first cover the opportunities that solution processing of the
powder offers, emphasizing the potential structural features that can be controlled
by precisely engineering the inorganic core of the particle, the surface, and
the organization of the particles before consolidation. We then discuss the challenges
of this synthetic approach and more practical matters related to solution processing.
Finally, we suggest some good practices for adequate knowledge transfer and improving
reproducibility among different laboratories.
acknowledgement: This work was financially supported by ISTA and the Werner Siemens
Foundation. M.C. has received funding from the European Union’s Horizon 2020 research
and innovation program under the Marie Skłodowska-Curie Grant Agreement no. 665385.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Christine
full_name: Fiedler, Christine
id: bd3fceba-dc74-11ea-a0a7-c17f71817366
last_name: Fiedler
- first_name: Tobias
full_name: Kleinhanns, Tobias
id: 8BD9DE16-AB3C-11E9-9C8C-2A03E6697425
last_name: Kleinhanns
orcid: 0000-0003-1537-7436
- first_name: Maria
full_name: Garcia, Maria
id: 6e5c50b8-97dc-11ed-be98-b0a74c84cae0
last_name: Garcia
- first_name: Seungho
full_name: Lee, Seungho
id: BB243B88-D767-11E9-B658-BC13E6697425
last_name: Lee
orcid: 0000-0002-6962-8598
- first_name: Mariano
full_name: Calcabrini, Mariano
id: 45D7531A-F248-11E8-B48F-1D18A9856A87
last_name: Calcabrini
orcid: 0000-0003-4566-5877
- first_name: Maria
full_name: Ibáñez, Maria
id: 43C61214-F248-11E8-B48F-1D18A9856A87
last_name: Ibáñez
orcid: 0000-0001-5013-2843
citation:
ama: 'Fiedler C, Kleinhanns T, Garcia M, Lee S, Calcabrini M, Ibáñez M. Solution-processed
inorganic thermoelectric materials: Opportunities and challenges ∇. Chemistry
of Materials. 2022;34(19):8471-8489. doi:10.1021/acs.chemmater.2c01967'
apa: 'Fiedler, C., Kleinhanns, T., Garcia, M., Lee, S., Calcabrini, M., & Ibáñez,
M. (2022). Solution-processed inorganic thermoelectric materials: Opportunities
and challenges ∇. Chemistry of Materials. American Chemical Society. https://doi.org/10.1021/acs.chemmater.2c01967'
chicago: 'Fiedler, Christine, Tobias Kleinhanns, Maria Garcia, Seungho Lee, Mariano
Calcabrini, and Maria Ibáñez. “Solution-Processed Inorganic Thermoelectric Materials:
Opportunities and Challenges ∇.” Chemistry of Materials. American Chemical
Society, 2022. https://doi.org/10.1021/acs.chemmater.2c01967.'
ieee: 'C. Fiedler, T. Kleinhanns, M. Garcia, S. Lee, M. Calcabrini, and M. Ibáñez,
“Solution-processed inorganic thermoelectric materials: Opportunities and challenges
∇,” Chemistry of Materials, vol. 34, no. 19. American Chemical Society,
pp. 8471–8489, 2022.'
ista: 'Fiedler C, Kleinhanns T, Garcia M, Lee S, Calcabrini M, Ibáñez M. 2022. Solution-processed
inorganic thermoelectric materials: Opportunities and challenges ∇. Chemistry
of Materials. 34(19), 8471–8489.'
mla: 'Fiedler, Christine, et al. “Solution-Processed Inorganic Thermoelectric Materials:
Opportunities and Challenges ∇.” Chemistry of Materials, vol. 34, no. 19,
American Chemical Society, 2022, pp. 8471–89, doi:10.1021/acs.chemmater.2c01967.'
short: C. Fiedler, T. Kleinhanns, M. Garcia, S. Lee, M. Calcabrini, M. Ibáñez, Chemistry
of Materials 34 (2022) 8471–8489.
corr_author: '1'
date_created: 2023-01-16T09:51:26Z
date_published: 2022-09-20T00:00:00Z
date_updated: 2026-08-11T12:39:14Z
day: '20'
ddc:
- '540'
department:
- _id: MaIb
doi: 10.1021/acs.chemmater.2c01967
ec_funded: 1
external_id:
isi:
- '000917837600001'
pmid:
- '36248227'
file:
- access_level: open_access
checksum: f7143e44ab510519d1949099c3558532
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T07:35:09Z
date_updated: 2023-01-30T07:35:09Z
file_id: '12434'
file_name: 2022_ChemistryMaterials_Fiedler.pdf
file_size: 10923495
relation: main_file
success: 1
file_date_updated: 2023-01-30T07:35:09Z
has_accepted_license: '1'
intvolume: ' 34'
isi: 1
issue: '19'
keyword:
- Materials Chemistry
- General Chemical Engineering
- General Chemistry
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 8471-8489
pmid: 1
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Chemistry of Materials
publication_identifier:
eissn:
- 1520-5002
issn:
- 0897-4756
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
related_material:
record:
- id: '20415'
relation: dissertation_contains
status: public
- id: '12885'
relation: dissertation_contains
status: public
- id: '22017'
relation: dissertation_contains
status: public
- id: '22626'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: 'Solution-processed inorganic thermoelectric materials: Opportunities and challenges
∇'
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: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2022'
...
---
_id: '11700'
abstract:
- lang: eng
text: This paper contains two contributions in the study of optimal transport on
metric graphs. Firstly, we prove a Benamou–Brenier formula for the Wasserstein
distance, which establishes the equivalence of static and dynamical optimal transport.
Secondly, in the spirit of Jordan–Kinderlehrer–Otto, we show that McKean–Vlasov
equations can be formulated as gradient flow of the free energy in the Wasserstein
space of probability measures. The proofs of these results are based on careful
regularisation arguments to circumvent some of the difficulties arising in metric
graphs, namely, branching of geodesics and the failure of semi-convexity of entropy
functionals in the Wasserstein space.
acknowledgement: "ME acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG),
Grant SFB 1283/2 2021 – 317210226. DF and JM were supported by the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 716117). JM also acknowledges support by the Austrian Science
Fund (FWF), Project SFB F65. The work of DM was partially supported by the Deutsche
Forschungsgemeinschaft\r\n(DFG), Grant 397230547. This article is based upon work
from COST Action\r\n18232 MAT-DYN-NET, supported by COST (European Cooperation in
Science\r\nand Technology), www.cost.eu. We wish to thank Martin Burger and Jan-Frederik\r\nPietschmann
for useful discussions. We are grateful to the anonymous referees for\r\ntheir careful
reading and useful suggestions."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Matthias
full_name: Erbar, Matthias
last_name: Erbar
- first_name: Dominik L
full_name: Forkert, Dominik L
id: 35C79D68-F248-11E8-B48F-1D18A9856A87
last_name: Forkert
- first_name: Jan
full_name: Maas, Jan
id: 4C5696CE-F248-11E8-B48F-1D18A9856A87
last_name: Maas
orcid: 0000-0002-0845-1338
- first_name: Delio
full_name: Mugnolo, Delio
last_name: Mugnolo
citation:
ama: Erbar M, Forkert DL, Maas J, Mugnolo D. Gradient flow formulation of diffusion
equations in the Wasserstein space over a metric graph. Networks and Heterogeneous
Media. 2022;17(5):687-717. doi:10.3934/nhm.2022023
apa: Erbar, M., Forkert, D. L., Maas, J., & Mugnolo, D. (2022). Gradient flow
formulation of diffusion equations in the Wasserstein space over a metric graph.
Networks and Heterogeneous Media. AIMS. https://doi.org/10.3934/nhm.2022023
chicago: Erbar, Matthias, Dominik L Forkert, Jan Maas, and Delio Mugnolo. “Gradient
Flow Formulation of Diffusion Equations in the Wasserstein Space over a Metric
Graph.” Networks and Heterogeneous Media. AIMS, 2022. https://doi.org/10.3934/nhm.2022023.
ieee: M. Erbar, D. L. Forkert, J. Maas, and D. Mugnolo, “Gradient flow formulation
of diffusion equations in the Wasserstein space over a metric graph,” Networks
and Heterogeneous Media, vol. 17, no. 5. AIMS, pp. 687–717, 2022.
ista: Erbar M, Forkert DL, Maas J, Mugnolo D. 2022. Gradient flow formulation of
diffusion equations in the Wasserstein space over a metric graph. Networks and
Heterogeneous Media. 17(5), 687–717.
mla: Erbar, Matthias, et al. “Gradient Flow Formulation of Diffusion Equations in
the Wasserstein Space over a Metric Graph.” Networks and Heterogeneous Media,
vol. 17, no. 5, AIMS, 2022, pp. 687–717, doi:10.3934/nhm.2022023.
short: M. Erbar, D.L. Forkert, J. Maas, D. Mugnolo, Networks and Heterogeneous Media
17 (2022) 687–717.
corr_author: '1'
date_created: 2022-07-31T22:01:46Z
date_published: 2022-10-01T00:00:00Z
date_updated: 2026-08-12T06:20:30Z
day: '01'
department:
- _id: JaMa
doi: 10.3934/nhm.2022023
ec_funded: 1
external_id:
arxiv:
- '2105.05677'
isi:
- '000812422100001'
intvolume: ' 17'
isi: 1
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2105.05677
month: '10'
oa: 1
oa_version: Preprint
page: 687-717
project:
- _id: 256E75B8-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '716117'
name: Optimal Transport and Stochastic Dynamics
- _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2
grant_number: F6504
name: Taming Complexity in Partial Differential Systems
publication: Networks and Heterogeneous Media
publication_identifier:
eissn:
- 1556-181X
issn:
- 1556-1801
publication_status: published
publisher: AIMS
quality_controlled: '1'
scopus_import: '1'
status: public
title: Gradient flow formulation of diffusion equations in the Wasserstein space over
a metric graph
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2022'
...
---
_id: '12299'
abstract:
- lang: eng
text: 'Transfer learning is a classic paradigm by which models pretrained on large
“upstream” datasets are adapted to yield good results on “downstream” specialized
datasets. Generally, more accurate models on the “upstream” dataset tend to provide
better transfer accuracy “downstream”. In this work, we perform an in-depth investigation
of this phenomenon in the context of convolutional neural networks (CNNs) trained
on the ImageNet dataset, which have been pruned-that is, compressed by sparsifiying
their connections. We consider transfer using unstructured pruned models obtained
by applying several state-of-the-art pruning methods, including magnitude-based,
second-order, regrowth, lottery-ticket, and regularization approaches, in the
context of twelve standard transfer tasks. In a nutshell, our study shows that
sparse models can match or even outperform the transfer performance of dense models,
even at high sparsities, and, while doing so, can lead to significant inference
and even training speedups. At the same time, we observe and analyze significant
differences in the behaviour of different pruning methods. The code is available
at: https://github.com/IST-DASLab/sparse-imagenet-transfer.'
acknowledgement: he authors would like to sincerely thank Christoph Lampert and Nir
Shavit for fruitful discussions during the development of this work, and Eldar Kurtic
for experimental support. EI was supported in part by the FWF DK VGSCO, grant agreement
number W1260-N35, while AP and DA acknowledge generous support by the ERC, via Starting
Grant 805223 ScaleML.
article_processing_charge: No
arxiv: 1
author:
- first_name: Eugenia B
full_name: Iofinova, Eugenia B
id: f9a17499-f6e0-11ea-865d-fdf9a3f77117
last_name: Iofinova
orcid: 0000-0002-7778-3221
- first_name: Elena-Alexandra
full_name: Peste, Elena-Alexandra
id: 32D78294-F248-11E8-B48F-1D18A9856A87
last_name: Peste
- first_name: Mark
full_name: Kurtz, Mark
last_name: Kurtz
- 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: 'Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. How well do sparse ImageNet
models transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern
Recognition. IEEE; 2022:12256-12266. doi:10.1109/cvpr52688.2022.01195'
apa: 'Iofinova, E. B., Krumes, A., Kurtz, M., & Alistarh, D.-A. (2022). How
well do sparse ImageNet models transfer? In 2022 IEEE/CVF Conference on Computer
Vision and Pattern Recognition (pp. 12256–12266). New Orleans, LA, United
States: IEEE. https://doi.org/10.1109/cvpr52688.2022.01195'
chicago: Iofinova, Eugenia B, Alexandra Krumes, Mark Kurtz, and Dan-Adrian Alistarh.
“How Well Do Sparse ImageNet Models Transfer?” In 2022 IEEE/CVF Conference
on Computer Vision and Pattern Recognition, 12256–66. IEEE, 2022. https://doi.org/10.1109/cvpr52688.2022.01195.
ieee: E. B. Iofinova, A. Krumes, M. Kurtz, and D.-A. Alistarh, “How well do sparse
ImageNet models transfer?,” in 2022 IEEE/CVF Conference on Computer Vision
and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 12256–12266.
ista: 'Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. 2022. How well do sparse ImageNet
models transfer? 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
CVPR: Computer Vision and Pattern Recognition, 12256–12266.'
mla: Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?”
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE,
2022, pp. 12256–66, doi:10.1109/cvpr52688.2022.01195.
short: E.B. Iofinova, A. Krumes, M. Kurtz, D.-A. Alistarh, in:, 2022 IEEE/CVF Conference
on Computer Vision and Pattern Recognition, IEEE, 2022, pp. 12256–12266.
conference:
end_date: 2022-06-24
location: New Orleans, LA, United States
name: 'CVPR: Computer Vision and Pattern Recognition'
start_date: 2022-06-18
corr_author: '1'
date_created: 2023-01-16T10:06:00Z
date_published: 2022-09-27T00:00:00Z
date_updated: 2026-08-12T06:34:08Z
day: '27'
department:
- _id: DaAl
- _id: ChLa
doi: 10.1109/cvpr52688.2022.01195
ec_funded: 1
external_id:
arxiv:
- '2111.13445'
isi:
- '000870759105034'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2111.13445
month: '09'
oa: 1
oa_version: Preprint
page: 12256-12266
project:
- _id: 9B9290DE-BA93-11EA-9121-9846C619BF3A
grant_number: W1260-N35
name: Vienna Graduate School on Computational Optimization
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition
publication_identifier:
eissn:
- 2575-7075
publication_status: published
publisher: IEEE
quality_controlled: '1'
related_material:
record:
- id: '13074'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: How well do sparse ImageNet models transfer?
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12161'
abstract:
- lang: eng
text: 'We introduce LIMES, a new method for learning with non-stationary streaming
data, inspired by the recent success of meta-learning. The main idea is not to
attempt to learn a single classifier that would have to work well across all occurring
data distributions, nor many separate classifiers, but to exploit a hybrid strategy:
we learn a single set of model parameters from which a specific classifier for
any specific data distribution is derived via classifier adaptation. Assuming
a multiclass classification setting with class-prior shift, the adaptation step
can be performed analytically with only the classifier’s bias terms being affected.
Another contribution of our work is an extrapolation step that predicts suitable
adaptation parameters for future time steps based on the previous data. In combination,
we obtain a lightweight procedure for learning from streaming data with varying
class distribution that adds no trainable parameters and almost no memory or computational
overhead compared to training a single model. Experiments on a set of exemplary
tasks using Twitter data show that LIMES achieves higher accuracy than alternative
approaches, especially with respect to the relevant real-world metric of lowest
within-day accuracy.'
article_processing_charge: No
arxiv: 1
author:
- first_name: Paulina
full_name: Tomaszewska, Paulina
last_name: Tomaszewska
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Tomaszewska P, Lampert C. Lightweight conditional model extrapolation for
streaming data under class-prior shift. In: 26th International Conference on
Pattern Recognition. Vol 2022. IEEE; 2022:2128-2134. doi:10.1109/icpr56361.2022.9956195'
apa: 'Tomaszewska, P., & Lampert, C. (2022). Lightweight conditional model extrapolation
for streaming data under class-prior shift. In 26th International Conference
on Pattern Recognition (Vol. 2022, pp. 2128–2134). Montreal, Canada: IEEE.
https://doi.org/10.1109/icpr56361.2022.9956195'
chicago: Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model
Extrapolation for Streaming Data under Class-Prior Shift.” In 26th International
Conference on Pattern Recognition, 2022:2128–34. IEEE, 2022. https://doi.org/10.1109/icpr56361.2022.9956195.
ieee: P. Tomaszewska and C. Lampert, “Lightweight conditional model extrapolation
for streaming data under class-prior shift,” in 26th International Conference
on Pattern Recognition, Montreal, Canada, 2022, vol. 2022, pp. 2128–2134.
ista: 'Tomaszewska P, Lampert C. 2022. Lightweight conditional model extrapolation
for streaming data under class-prior shift. 26th International Conference on Pattern
Recognition. ICPR: International Conference on Pattern Recognition vol. 2022,
2128–2134.'
mla: Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model
Extrapolation for Streaming Data under Class-Prior Shift.” 26th International
Conference on Pattern Recognition, vol. 2022, IEEE, 2022, pp. 2128–34, doi:10.1109/icpr56361.2022.9956195.
short: P. Tomaszewska, C. Lampert, in:, 26th International Conference on Pattern
Recognition, IEEE, 2022, pp. 2128–2134.
conference:
end_date: 2022-08-25
location: Montreal, Canada
name: 'ICPR: International Conference on Pattern Recognition'
start_date: 2022-08-21
corr_author: '1'
date_created: 2023-01-12T12:09:38Z
date_published: 2022-11-29T00:00:00Z
date_updated: 2026-08-12T06:35:14Z
day: '29'
department:
- _id: ChLa
doi: 10.1109/icpr56361.2022.9956195
external_id:
arxiv:
- '2206.05181'
isi:
- '000897707602018'
intvolume: ' 2022'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2206.05181
month: '11'
oa: 1
oa_version: Preprint
page: 2128-2134
publication: 26th International Conference on Pattern Recognition
publication_identifier:
eisbn:
- '9781665490627'
eissn:
- 2831-7475
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Lightweight conditional model extrapolation for streaming data under class-prior
shift
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
_id: '12160'
abstract:
- lang: eng
text: We present the Filecoin Hierarchical Consensus framework, which aims to overcome
the throughput challenges of blockchain consensus by horizontally scaling the
network. Unlike traditional sharding designs, based on partitioning the state
of the network, our solution centers on the concept of subnets -which are organized
hierarchically- and can be spawned on-demand to manage new state. Child sub nets
are firewalled from parent subnets, have their own specific policies, and run
a different consensus algorithm, increasing the network capacity and enabling
new applications. Moreover, they benefit from the security of parent subnets by
periodically checkpointing state. In this paper, we introduce the overall system
architecture, our detailed designs for cross-net transaction handling, and the
open questions that we are still exploring.
article_processing_charge: No
author:
- first_name: Alfonso
full_name: De la Rocha, Alfonso
last_name: De la Rocha
- first_name: Eleftherios
full_name: Kokoris Kogias, Eleftherios
id: f5983044-d7ef-11ea-ac6d-fd1430a26d30
last_name: Kokoris Kogias
orcid: 0000-0002-8827-3382
- first_name: Jorge M.
full_name: Soares, Jorge M.
last_name: Soares
- first_name: Marko
full_name: Vukolic, Marko
last_name: Vukolic
citation:
ama: 'De la Rocha A, Kokoris Kogias E, Soares JM, Vukolic M. Hierarchical consensus:
A horizontal scaling framework for blockchains. In: 42nd International Conference
on Distributed Computing Systems Workshops. Vol 2022. IEEE; 2022:45-52. doi:10.1109/icdcsw56584.2022.00018'
apa: 'De la Rocha, A., Kokoris Kogias, E., Soares, J. M., & Vukolic, M. (2022).
Hierarchical consensus: A horizontal scaling framework for blockchains. In 42nd
International Conference on Distributed Computing Systems Workshops (Vol.
2022, pp. 45–52). Bologna, Italy: IEEE. https://doi.org/10.1109/icdcsw56584.2022.00018'
chicago: 'De la Rocha, Alfonso, Eleftherios Kokoris Kogias, Jorge M. Soares, and
Marko Vukolic. “Hierarchical Consensus: A Horizontal Scaling Framework for Blockchains.”
In 42nd International Conference on Distributed Computing Systems Workshops,
2022:45–52. IEEE, 2022. https://doi.org/10.1109/icdcsw56584.2022.00018.'
ieee: 'A. De la Rocha, E. Kokoris Kogias, J. M. Soares, and M. Vukolic, “Hierarchical
consensus: A horizontal scaling framework for blockchains,” in 42nd International
Conference on Distributed Computing Systems Workshops, Bologna, Italy, 2022,
vol. 2022, pp. 45–52.'
ista: 'De la Rocha A, Kokoris Kogias E, Soares JM, Vukolic M. 2022. Hierarchical
consensus: A horizontal scaling framework for blockchains. 42nd International
Conference on Distributed Computing Systems Workshops. ICDCSW: International Conference
on Distributed Computing Systems Workshop vol. 2022, 45–52.'
mla: 'De la Rocha, Alfonso, et al. “Hierarchical Consensus: A Horizontal Scaling
Framework for Blockchains.” 42nd International Conference on Distributed Computing
Systems Workshops, vol. 2022, IEEE, 2022, pp. 45–52, doi:10.1109/icdcsw56584.2022.00018.'
short: A. De la Rocha, E. Kokoris Kogias, J.M. Soares, M. Vukolic, in:, 42nd International
Conference on Distributed Computing Systems Workshops, IEEE, 2022, pp. 45–52.
conference:
end_date: 2022-07-10
location: Bologna, Italy
name: 'ICDCSW: International Conference on Distributed Computing Systems Workshop'
start_date: 2022-07-10
date_created: 2023-01-12T12:09:28Z
date_published: 2022-11-29T00:00:00Z
date_updated: 2026-08-12T06:34:42Z
day: '29'
department:
- _id: ElKo
doi: 10.1109/icdcsw56584.2022.00018
external_id:
isi:
- '000895984800009'
intvolume: ' 2022'
isi: 1
language:
- iso: eng
month: '11'
oa_version: None
page: 45-52
publication: 42nd International Conference on Distributed Computing Systems Workshops
publication_identifier:
eisbn:
- '9781665488792'
eissn:
- 2332-5666
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Hierarchical consensus: A horizontal scaling framework for blockchains'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
_id: '12432'
abstract:
- lang: eng
text: "We present CertifyHAM, a deterministic algorithm that takes a graph G as
input and either finds a Hamilton cycle of G or outputs that such a cycle does
not exist. If G ∼ G(n, p) and p ≥\r\n100 log n/n then the expected running time
of CertifyHAM is O(n/p) which is best possible. This improves upon previous results
due to Gurevich and Shelah, Thomason and Alon, and\r\nKrivelevich, who proved
analogous results for p being constant, p ≥ 12n −1/3 and p ≥ 70n\r\n−1/2 respectively."
acknowledgement: "This project has received funding from the European Union’s Horizon
2020\r\nresearch and innovation programme under the Marie Skłodowska-Curie grant\r\nagreement
No 101034413"
article_processing_charge: No
author:
- first_name: Michael
full_name: Anastos, Michael
id: 0b2a4358-bb35-11ec-b7b9-e3279b593dbb
last_name: Anastos
citation:
ama: 'Anastos M. Solving the Hamilton cycle problem fast on average. In: 63rd
Annual IEEE Symposium on Foundations of Computer Science. Vol 2022-October.
IEEE; 2022:919-930. doi:10.1109/FOCS54457.2022.00091'
apa: 'Anastos, M. (2022). Solving the Hamilton cycle problem fast on average. In
63rd Annual IEEE Symposium on Foundations of Computer Science (Vol. 2022–October,
pp. 919–930). Denver, CO, United States: IEEE. https://doi.org/10.1109/FOCS54457.2022.00091'
chicago: Anastos, Michael. “Solving the Hamilton Cycle Problem Fast on Average.”
In 63rd Annual IEEE Symposium on Foundations of Computer Science, 2022–October:919–30.
IEEE, 2022. https://doi.org/10.1109/FOCS54457.2022.00091.
ieee: M. Anastos, “Solving the Hamilton cycle problem fast on average,” in 63rd
Annual IEEE Symposium on Foundations of Computer Science, Denver, CO, United
States, 2022, vol. 2022–October, pp. 919–930.
ista: 'Anastos M. 2022. Solving the Hamilton cycle problem fast on average. 63rd
Annual IEEE Symposium on Foundations of Computer Science. FOCS: Foundations of
Computer Science vol. 2022–October, 919–930.'
mla: Anastos, Michael. “Solving the Hamilton Cycle Problem Fast on Average.” 63rd
Annual IEEE Symposium on Foundations of Computer Science, vol. 2022–October,
IEEE, 2022, pp. 919–30, doi:10.1109/FOCS54457.2022.00091.
short: M. Anastos, in:, 63rd Annual IEEE Symposium on Foundations of Computer Science,
IEEE, 2022, pp. 919–930.
conference:
end_date: 2022-11-03
location: Denver, CO, United States
name: 'FOCS: Foundations of Computer Science'
start_date: 2022-10-31
corr_author: '1'
date_created: 2023-01-29T23:00:59Z
date_published: 2022-12-01T00:00:00Z
date_updated: 2026-08-12T06:34:24Z
day: '01'
department:
- _id: MaKw
doi: 10.1109/FOCS54457.2022.00091
ec_funded: 1
external_id:
isi:
- '000909382900084'
isi: 1
language:
- iso: eng
month: '12'
oa_version: None
page: 919-930
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: 63rd Annual IEEE Symposium on Foundations of Computer Science
publication_identifier:
isbn:
- '9781665455190'
issn:
- 0272-5428
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Solving the Hamilton cycle problem fast on average
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022-October
year: '2022'
...
---
_id: '12017'
abstract:
- lang: eng
text: 'In the classic adversarial communication problem, two parties communicate
over a noisy channel in the presence of a malicious jamming adversary. The arbitrarily
varying channels (AVCs) offer an elegant framework to study a wide range of interesting
adversary models. The optimal throughput or capacity over such AVCs is intimately
tied to the underlying adversary model; in some cases, capacity is unknown and
the problem is known to be notoriously hard. The omniscient adversary, one which
knows the sender’s entire channel transmission a priori, is one of such classic
models of interest; the capacity under such an adversary remains an exciting open
problem. The myopic adversary is a generalization of that model where the adversary’s
observation may be corrupted over a noisy discrete memoryless channel. Through
the adversary’s myopicity, one can unify the slew of different adversary models,
ranging from the omniscient adversary to one that is completely blind to the transmission
(the latter is the well known oblivious model where the capacity is fully characterized).In
this work, we present new results on the capacity under both the omniscient and
myopic adversary models. We completely characterize the positive capacity threshold
over general AVCs with omniscient adversaries. The characterization is in terms
of two key combinatorial objects: the set of completely positive distributions
and the CP-confusability set. For omniscient AVCs with positive capacity, we present
non-trivial lower and upper bounds on the capacity; unlike some of the previous
bounds, our bounds hold under fairly general input and jamming constraints. Our
lower bound improves upon the generalized Gilbert-Varshamov bound for general
AVCs while the upper bound generalizes the well known Elias-Bassalygo bound (known
for binary and q-ary alphabets). For the myopic AVCs, we build on prior results
known for the so-called sufficiently myopic model, and present new results on
the positive rate communication threshold over the so-called insufficiently myopic
regime (a completely insufficient myopic adversary specializes to an omniscient
adversary). We present interesting examples for the widely studied models of adversarial
bit-flip and bit-erasure channels. In fact, for the bit-flip AVC with additive
adversarial noise as well as random noise, we completely characterize the omniscient
model capacity when the random noise is sufficiently large vis-a-vis the adversary’s
budget.'
article_processing_charge: No
author:
- first_name: Anuj Kumar
full_name: Yadav, Anuj Kumar
last_name: Yadav
- first_name: Mohammadreza
full_name: Alimohammadi, Mohammadreza
last_name: Alimohammadi
- first_name: Yihan
full_name: Zhang, Yihan
id: 2ce5da42-b2ea-11eb-bba5-9f264e9d002c
last_name: Zhang
orcid: 0000-0002-6465-6258
- first_name: Amitalok J.
full_name: Budkuley, Amitalok J.
last_name: Budkuley
- first_name: Sidharth
full_name: Jaggi, Sidharth
last_name: Jaggi
citation:
ama: 'Yadav AK, Alimohammadi M, Zhang Y, Budkuley AJ, Jaggi S. New results on AVCs
with omniscient and myopic adversaries. In: 2022 IEEE International Symposium
on Information Theory. Vol 2022. IEEE; 2022:2535-2540. doi:10.1109/ISIT50566.2022.9834632'
apa: 'Yadav, A. K., Alimohammadi, M., Zhang, Y., Budkuley, A. J., & Jaggi, S.
(2022). New results on AVCs with omniscient and myopic adversaries. In 2022
IEEE International Symposium on Information Theory (Vol. 2022, pp. 2535–2540).
Espoo, Finland: IEEE. https://doi.org/10.1109/ISIT50566.2022.9834632'
chicago: Yadav, Anuj Kumar, Mohammadreza Alimohammadi, Yihan Zhang, Amitalok J.
Budkuley, and Sidharth Jaggi. “New Results on AVCs with Omniscient and Myopic
Adversaries.” In 2022 IEEE International Symposium on Information Theory,
2022:2535–40. IEEE, 2022. https://doi.org/10.1109/ISIT50566.2022.9834632.
ieee: A. K. Yadav, M. Alimohammadi, Y. Zhang, A. J. Budkuley, and S. Jaggi, “New
results on AVCs with omniscient and myopic adversaries,” in 2022 IEEE International
Symposium on Information Theory, Espoo, Finland, 2022, vol. 2022, pp. 2535–2540.
ista: 'Yadav AK, Alimohammadi M, Zhang Y, Budkuley AJ, Jaggi S. 2022. New results
on AVCs with omniscient and myopic adversaries. 2022 IEEE International Symposium
on Information Theory. ISIT: Internation Symposium on Information Theory vol.
2022, 2535–2540.'
mla: Yadav, Anuj Kumar, et al. “New Results on AVCs with Omniscient and Myopic Adversaries.”
2022 IEEE International Symposium on Information Theory, vol. 2022, IEEE,
2022, pp. 2535–40, doi:10.1109/ISIT50566.2022.9834632.
short: A.K. Yadav, M. Alimohammadi, Y. Zhang, A.J. Budkuley, S. Jaggi, in:, 2022
IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2535–2540.
conference:
end_date: 2022-07-01
location: Espoo, Finland
name: 'ISIT: Internation Symposium on Information Theory'
start_date: 2022-06-26
date_created: 2022-09-04T22:02:06Z
date_published: 2022-08-03T00:00:00Z
date_updated: 2026-08-12T06:36:54Z
day: '03'
department:
- _id: MaMo
doi: 10.1109/ISIT50566.2022.9834632
external_id:
isi:
- '001254261902116'
intvolume: ' 2022'
isi: 1
language:
- iso: eng
month: '08'
oa_version: None
page: 2535-2540
publication: 2022 IEEE International Symposium on Information Theory
publication_identifier:
isbn:
- '9781665421591'
issn:
- 2157-8095
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: New results on AVCs with omniscient and myopic adversaries
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
_id: '12018'
abstract:
- lang: eng
text: We study the problem of characterizing the maximal rates of list decoding
in Euclidean spaces for finite list sizes. For any positive integer L ≥ 2 and
real N > 0, we say that a subset C⊂Rn is an (N,L – 1)-multiple packing or an (N,L–
1)-list decodable code if every Euclidean ball of radius nN−−−√ in ℝ n contains
no more than L − 1 points of C. We study this problem with and without ℓ 2 norm
constraints on C, and derive the best-known lower bounds on the maximal rate for
(N,L−1) multiple packing. Our bounds are obtained via error exponents for list
decoding over Additive White Gaussian Noise (AWGN) channels. We establish a curious
inequality which relates the error exponent, a quantity of average-case nature,
to the list-decoding radius, a quantity of worst-case nature. We derive various
bounds on the error exponent for list decoding in both bounded and unbounded settings
which could be of independent interest beyond multiple packing.
article_processing_charge: No
author:
- first_name: Yihan
full_name: Zhang, Yihan
id: 2ce5da42-b2ea-11eb-bba5-9f264e9d002c
last_name: Zhang
orcid: 0000-0002-6465-6258
- first_name: Shashank
full_name: Vatedka, Shashank
last_name: Vatedka
citation:
ama: 'Zhang Y, Vatedka S. Lower bounds on list decoding capacity using error exponents.
In: 2022 IEEE International Symposium on Information Theory. Vol 2022.
IEEE; 2022:1324-1329. doi:10.1109/ISIT50566.2022.9834815'
apa: 'Zhang, Y., & Vatedka, S. (2022). Lower bounds on list decoding capacity
using error exponents. In 2022 IEEE International Symposium on Information
Theory (Vol. 2022, pp. 1324–1329). Espoo, Finland: IEEE. https://doi.org/10.1109/ISIT50566.2022.9834815'
chicago: Zhang, Yihan, and Shashank Vatedka. “Lower Bounds on List Decoding Capacity
Using Error Exponents.” In 2022 IEEE International Symposium on Information
Theory, 2022:1324–29. IEEE, 2022. https://doi.org/10.1109/ISIT50566.2022.9834815.
ieee: Y. Zhang and S. Vatedka, “Lower bounds on list decoding capacity using error
exponents,” in 2022 IEEE International Symposium on Information Theory,
Espoo, Finland, 2022, vol. 2022, pp. 1324–1329.
ista: 'Zhang Y, Vatedka S. 2022. Lower bounds on list decoding capacity using error
exponents. 2022 IEEE International Symposium on Information Theory. ISIT: International
Symposium on Information Theory vol. 2022, 1324–1329.'
mla: Zhang, Yihan, and Shashank Vatedka. “Lower Bounds on List Decoding Capacity
Using Error Exponents.” 2022 IEEE International Symposium on Information Theory,
vol. 2022, IEEE, 2022, pp. 1324–29, doi:10.1109/ISIT50566.2022.9834815.
short: Y. Zhang, S. Vatedka, in:, 2022 IEEE International Symposium on Information
Theory, IEEE, 2022, pp. 1324–1329.
conference:
end_date: 2022-07-01
location: Espoo, Finland
name: 'ISIT: International Symposium on Information Theory'
start_date: 2022-06-26
date_created: 2022-09-04T22:02:06Z
date_published: 2022-08-03T00:00:00Z
date_updated: 2026-08-12T06:37:09Z
day: '03'
department:
- _id: MaMo
doi: 10.1109/ISIT50566.2022.9834815
external_id:
isi:
- '001254261901080'
intvolume: ' 2022'
isi: 1
language:
- iso: eng
month: '08'
oa_version: None
page: 1324-1329
publication: 2022 IEEE International Symposium on Information Theory
publication_identifier:
isbn:
- '9781665421591'
issn:
- 2157-8095
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Lower bounds on list decoding capacity using error exponents
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
_id: '12019'
abstract:
- lang: eng
text: This paper studies combinatorial properties of codes for the Z-channel. A
Z-channel with error fraction τ takes as input a length-n binary codeword and
injects in an adversarial manner up to nτ asymmetric errors, i.e., errors that
only zero out bits but do not flip 0’s to 1’s. It is known that the largest (L
− 1)-list-decodable code for the Z-channel with error fraction τ has exponential
(in n) size if τ is less than a critical value that we call the Plotkin point
and has constant size if τ is larger than the threshold. The (L−1)-list-decoding
Plotkin point is known to be L−1L−1−L−LL−1. In this paper, we show that the largest
(L−1)-list-decodable code ε-above the Plotkin point has size Θ L (ε −3/2 ) for
any L − 1 ≥ 1.
article_processing_charge: No
author:
- first_name: Nikita
full_name: Polyanskii, Nikita
last_name: Polyanskii
- first_name: Yihan
full_name: Zhang, Yihan
id: 2ce5da42-b2ea-11eb-bba5-9f264e9d002c
last_name: Zhang
orcid: 0000-0002-6465-6258
citation:
ama: 'Polyanskii N, Zhang Y. List-decodable zero-rate codes for the Z-channel. In:
2022 IEEE International Symposium on Information Theory. Vol 2022. IEEE;
2022:2553-2558. doi:10.1109/ISIT50566.2022.9834829'
apa: 'Polyanskii, N., & Zhang, Y. (2022). List-decodable zero-rate codes for
the Z-channel. In 2022 IEEE International Symposium on Information Theory
(Vol. 2022, pp. 2553–2558). Espoo, Finland: IEEE. https://doi.org/10.1109/ISIT50566.2022.9834829'
chicago: Polyanskii, Nikita, and Yihan Zhang. “List-Decodable Zero-Rate Codes for
the Z-Channel.” In 2022 IEEE International Symposium on Information Theory,
2022:2553–58. IEEE, 2022. https://doi.org/10.1109/ISIT50566.2022.9834829.
ieee: N. Polyanskii and Y. Zhang, “List-decodable zero-rate codes for the Z-channel,”
in 2022 IEEE International Symposium on Information Theory, Espoo, Finland,
2022, vol. 2022, pp. 2553–2558.
ista: 'Polyanskii N, Zhang Y. 2022. List-decodable zero-rate codes for the Z-channel.
2022 IEEE International Symposium on Information Theory. ISIT: International Symposium
on Information Theory vol. 2022, 2553–2558.'
mla: Polyanskii, Nikita, and Yihan Zhang. “List-Decodable Zero-Rate Codes for the
Z-Channel.” 2022 IEEE International Symposium on Information Theory, vol.
2022, IEEE, 2022, pp. 2553–58, doi:10.1109/ISIT50566.2022.9834829.
short: N. Polyanskii, Y. Zhang, in:, 2022 IEEE International Symposium on Information
Theory, IEEE, 2022, pp. 2553–2558.
conference:
end_date: 2022-07-01
location: Espoo, Finland
name: 'ISIT: International Symposium on Information Theory'
start_date: 2022-06-26
date_created: 2022-09-04T22:02:07Z
date_published: 2022-08-03T00:00:00Z
date_updated: 2026-08-12T06:37:29Z
day: '03'
department:
- _id: MaMo
doi: 10.1109/ISIT50566.2022.9834829
external_id:
isi:
- '001254261902119'
intvolume: ' 2022'
isi: 1
language:
- iso: eng
month: '08'
oa_version: None
page: 2553-2558
publication: 2022 IEEE International Symposium on Information Theory
publication_identifier:
isbn:
- '9781665421591'
issn:
- 2157-8095
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: List-decodable zero-rate codes for the Z-channel
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
OA_place: repository
_id: '11366'
abstract:
- lang: eng
text: "Adversarial training (i.e., training on adversarially perturbed input data)
is a well-studied method for making neural networks robust to potential adversarial
attacks during inference. However, the improved robustness does not\r\ncome for
free but rather is accompanied by a decrease in overall model accuracy and performance.
Recent work has shown that, in practical robot learning applications, the effects
of adversarial training do not pose a fair trade-off\r\nbut inflict a net loss
when measured in holistic robot performance. This work revisits the robustness-accuracy
trade-off in robot learning by systematically analyzing if recent advances in
robust training methods and theory in\r\nconjunction with adversarial robot learning
can make adversarial training suitable for real-world robot applications. We evaluate
a wide variety of robot learning tasks ranging from autonomous driving in a high-fidelity
environment\r\namenable to sim-to-real deployment, to mobile robot gesture recognition.
Our results demonstrate that, while these techniques make incremental improvements
on the trade-off on a relative scale, the negative side-effects caused by\r\nadversarial
training still outweigh the improvements by an order of magnitude. We conclude
that more substantial advances in robust learning methods are necessary before
they can benefit robot learning tasks in practice."
acknowledgement: "This work was supported in parts by the ERC-2020-AdG 101020093,
National Science Foundation (NSF), and JP\r\nMorgan Graduate Fellowships. We thank
Christoph Lampert for inspiring this work.\r\n"
article_number: '2204.07373'
article_processing_charge: No
arxiv: 1
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Alexander
full_name: Amini, Alexander
last_name: Amini
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy
tradeoff in robot learning. arXiv. doi:10.48550/arXiv.2204.07373
apa: Lechner, M., Amini, A., Rus, D., & Henzinger, T. A. (n.d.). Revisiting
the adversarial robustness-accuracy tradeoff in robot learning. arXiv.
https://doi.org/10.48550/arXiv.2204.07373
chicago: Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger.
“Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv,
n.d. https://doi.org/10.48550/arXiv.2204.07373.
ieee: M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial
robustness-accuracy tradeoff in robot learning,” arXiv. .
ista: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy
tradeoff in robot learning. arXiv, 2204.07373.
mla: Lechner, Mathias, et al. “Revisiting the Adversarial Robustness-Accuracy Tradeoff
in Robot Learning.” ArXiv, 2204.07373, doi:10.48550/arXiv.2204.07373.
short: M. Lechner, A. Amini, D. Rus, T.A. Henzinger, ArXiv (n.d.).
corr_author: '1'
date_created: 2022-05-12T13:20:17Z
date_published: 2022-04-15T00:00:00Z
date_updated: 2026-08-12T06:40:15Z
day: '15'
department:
- _id: ToHe
doi: 10.48550/arXiv.2204.07373
ec_funded: 1
external_id:
arxiv:
- '2204.07373'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2204.07373
month: '04'
oa: 1
oa_version: Preprint
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: arXiv
publication_status: draft
related_material:
record:
- id: '11362'
relation: dissertation_contains
status: public
- id: '12704'
relation: later_version
status: public
status: public
title: Revisiting the adversarial robustness-accuracy tradeoff in robot learning
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12300'
abstract:
- lang: eng
text: Distributed Key Generation (DKG) is a technique to bootstrap threshold cryptosystems
without a trusted third party and is a building block to decentralized protocols
such as randomness beacons, threshold signatures, and general multiparty computation.
Until recently, DKG protocols have assumed the synchronous model and thus are
vulnerable when their underlying network assumptions do not hold. The recent advancements
in asynchronous DKG protocols are insufficient as they either have poor efficiency
or limited functionality, resulting in a lack of concrete implementations. In
this paper, we present a simple and concretely efficient asynchronous DKG (ADKG)
protocol. In a network of n nodes, our ADKG protocol can tolerate up to t2022 IEEE Symposium on Security and Privacy.
IEEE; 2022:2518-2534. doi:10.1109/sp46214.2022.9833584'
apa: 'Das, S., Yurek, T., Xiang, Z., Miller, A., Kokoris Kogias, E., & Ren,
L. (2022). Practical asynchronous distributed key generation. In 2022 IEEE
Symposium on Security and Privacy (pp. 2518–2534). San Francisco, CA, United
States: IEEE. https://doi.org/10.1109/sp46214.2022.9833584'
chicago: Das, Sourav, Thomas Yurek, Zhuolun Xiang, Andrew Miller, Eleftherios Kokoris
Kogias, and Ling Ren. “Practical Asynchronous Distributed Key Generation.” In
2022 IEEE Symposium on Security and Privacy, 2518–34. IEEE, 2022. https://doi.org/10.1109/sp46214.2022.9833584.
ieee: S. Das, T. Yurek, Z. Xiang, A. Miller, E. Kokoris Kogias, and L. Ren, “Practical
asynchronous distributed key generation,” in 2022 IEEE Symposium on Security
and Privacy, San Francisco, CA, United States, 2022, pp. 2518–2534.
ista: 'Das S, Yurek T, Xiang Z, Miller A, Kokoris Kogias E, Ren L. 2022. Practical
asynchronous distributed key generation. 2022 IEEE Symposium on Security and Privacy.
SP: Symposium on Security and Privacy, 2518–2534.'
mla: Das, Sourav, et al. “Practical Asynchronous Distributed Key Generation.” 2022
IEEE Symposium on Security and Privacy, IEEE, 2022, pp. 2518–34, doi:10.1109/sp46214.2022.9833584.
short: S. Das, T. Yurek, Z. Xiang, A. Miller, E. Kokoris Kogias, L. Ren, in:, 2022
IEEE Symposium on Security and Privacy, IEEE, 2022, pp. 2518–2534.
conference:
end_date: 2022-05-26
location: San Francisco, CA, United States
name: 'SP: Symposium on Security and Privacy'
start_date: 2022-05-23
date_created: 2023-01-16T10:06:11Z
date_published: 2022-07-27T00:00:00Z
date_updated: 2026-08-12T06:40:50Z
day: '27'
department:
- _id: ElKo
doi: 10.1109/sp46214.2022.9833584
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2021/1591
month: '07'
oa: 1
oa_version: Preprint
page: 2518-2534
publication: 2022 IEEE Symposium on Security and Privacy
publication_identifier:
eisbn:
- '9781665413169'
eissn:
- 2375-1207
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Practical asynchronous distributed key generation
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12273'
abstract:
- lang: eng
text: We study communication in the presence of a jamming adversary where quadratic
power constraints are imposed on the transmitter and the jammer. The jamming signal
is allowed to be a function of the codebook, and a noncausal but noisy observation
of the transmitted codeword. For a certain range of the noise-to-signal ratios
(NSRs) of the transmitter and the jammer, we are able to characterize the capacity
of this channel under deterministic encoding or stochastic encoding, i.e., with
no common randomness between the encoder/decoder pair. For the remaining NSR regimes,
we determine the capacity under the assumption of a small amount of common randomness
(at most 2log(n) bits in one sub-regime, and at most Ω(n) bits in the other sub-regime)
available to the encoder-decoder pair. Our proof techniques involve a novel myopic
list-decoding result for achievability, and a Plotkin-type push attack for the
converse in a subregion of the NSRs, both of which may be of independent interest.
We also give bounds on the strong secrecy capacity of this channel assuming that
the jammer is simultaneously eavesdropping.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Yihan
full_name: Zhang, Yihan
id: 2ce5da42-b2ea-11eb-bba5-9f264e9d002c
last_name: Zhang
orcid: 0000-0002-6465-6258
- first_name: Shashank
full_name: Vatedka, Shashank
last_name: Vatedka
- first_name: Sidharth
full_name: Jaggi, Sidharth
last_name: Jaggi
- first_name: Anand D.
full_name: Sarwate, Anand D.
last_name: Sarwate
citation:
ama: Zhang Y, Vatedka S, Jaggi S, Sarwate AD. Quadratically constrained myopic adversarial
channels. IEEE Transactions on Information Theory. 2022;68(8):4901-4948.
doi:10.1109/tit.2022.3167554
apa: Zhang, Y., Vatedka, S., Jaggi, S., & Sarwate, A. D. (2022). Quadratically
constrained myopic adversarial channels. IEEE Transactions on Information Theory.
IEEE. https://doi.org/10.1109/tit.2022.3167554
chicago: Zhang, Yihan, Shashank Vatedka, Sidharth Jaggi, and Anand D. Sarwate. “Quadratically
Constrained Myopic Adversarial Channels.” IEEE Transactions on Information
Theory. IEEE, 2022. https://doi.org/10.1109/tit.2022.3167554.
ieee: Y. Zhang, S. Vatedka, S. Jaggi, and A. D. Sarwate, “Quadratically constrained
myopic adversarial channels,” IEEE Transactions on Information Theory,
vol. 68, no. 8. IEEE, pp. 4901–4948, 2022.
ista: Zhang Y, Vatedka S, Jaggi S, Sarwate AD. 2022. Quadratically constrained myopic
adversarial channels. IEEE Transactions on Information Theory. 68(8), 4901–4948.
mla: Zhang, Yihan, et al. “Quadratically Constrained Myopic Adversarial Channels.”
IEEE Transactions on Information Theory, vol. 68, no. 8, IEEE, 2022, pp.
4901–48, doi:10.1109/tit.2022.3167554.
short: Y. Zhang, S. Vatedka, S. Jaggi, A.D. Sarwate, IEEE Transactions on Information
Theory 68 (2022) 4901–4948.
corr_author: '1'
date_created: 2023-01-16T10:01:19Z
date_published: 2022-08-01T00:00:00Z
date_updated: 2026-08-12T06:41:20Z
day: '01'
department:
- _id: MaMo
doi: 10.1109/tit.2022.3167554
external_id:
arxiv:
- '1801.05951'
isi:
- '000838527100004'
intvolume: ' 68'
isi: 1
issue: '8'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.1801.05951
month: '08'
oa: 1
oa_version: Preprint
page: 4901-4948
publication: IEEE Transactions on Information Theory
publication_identifier:
eissn:
- 1557-9654
issn:
- 0018-9448
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quadratically constrained myopic adversarial channels
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 68
year: '2022'
...
---
_id: '12233'
abstract:
- lang: eng
text: A novel recursive list decoding (RLD) algorithm for Reed-Muller (RM) codes
based on successive permutations (SP) of the codeword is presented. A low-complexity
SP scheme applied to a subset of the symmetry group of RM codes is first proposed
to carefully select a good codeword permutation on the fly. Then, the proposed
SP technique is integrated into an improved RLD algorithm that initializes different
decoding paths with random codeword permutations, which are sampled from the full
symmetry group of RM codes. Finally, efficient latency and complexity reduction
schemes are introduced that virtually preserve the error-correction performance
of the proposed decoder. Simulation results demonstrate that at the target frame
error rate of 10−3 for the RM code of length 256 with 163 information bits, the
proposed decoder reduces 6% of the computational complexity and 22% of the decoding
latency of the state-of-the-art semi-parallel simplified successive-cancellation
decoder with fast Hadamard transform (SSC-FHT) that uses 96 permutations from
the full symmetry group of RM codes, while relatively maintaining the error-correction
performance and memory consumption of the semi-parallel permuted SSC-FHT decoder.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Nghia
full_name: Doan, Nghia
last_name: Doan
- first_name: Seyyed Ali
full_name: Hashemi, Seyyed Ali
last_name: Hashemi
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
- first_name: Warren J.
full_name: Gross, Warren J.
last_name: Gross
citation:
ama: Doan N, Hashemi SA, Mondelli M, Gross WJ. Decoding Reed-Muller codes with successive
codeword permutations. IEEE Transactions on Communications. 2022;70(11):7134-7145.
doi:10.1109/tcomm.2022.3211101
apa: Doan, N., Hashemi, S. A., Mondelli, M., & Gross, W. J. (2022). Decoding
Reed-Muller codes with successive codeword permutations. IEEE Transactions
on Communications. IEEE. https://doi.org/10.1109/tcomm.2022.3211101
chicago: Doan, Nghia, Seyyed Ali Hashemi, Marco Mondelli, and Warren J. Gross. “Decoding
Reed-Muller Codes with Successive Codeword Permutations.” IEEE Transactions
on Communications. IEEE, 2022. https://doi.org/10.1109/tcomm.2022.3211101.
ieee: N. Doan, S. A. Hashemi, M. Mondelli, and W. J. Gross, “Decoding Reed-Muller
codes with successive codeword permutations,” IEEE Transactions on Communications,
vol. 70, no. 11. IEEE, pp. 7134–7145, 2022.
ista: Doan N, Hashemi SA, Mondelli M, Gross WJ. 2022. Decoding Reed-Muller codes
with successive codeword permutations. IEEE Transactions on Communications. 70(11),
7134–7145.
mla: Doan, Nghia, et al. “Decoding Reed-Muller Codes with Successive Codeword Permutations.”
IEEE Transactions on Communications, vol. 70, no. 11, IEEE, 2022, pp. 7134–45,
doi:10.1109/tcomm.2022.3211101.
short: N. Doan, S.A. Hashemi, M. Mondelli, W.J. Gross, IEEE Transactions on Communications
70 (2022) 7134–7145.
date_created: 2023-01-16T09:50:38Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2026-08-12T06:41:04Z
day: '01'
department:
- _id: MaMo
doi: 10.1109/tcomm.2022.3211101
external_id:
arxiv:
- '2109.02122'
isi:
- '000937284600006'
intvolume: ' 70'
isi: 1
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.2109.02122'
month: '11'
oa: 1
oa_version: Preprint
page: 7134-7145
publication: IEEE Transactions on Communications
publication_identifier:
eissn:
- 1558-0857
issn:
- 0090-6778
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Decoding Reed-Muller codes with successive codeword permutations
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 70
year: '2022'
...
---
_id: '10364'
abstract:
- lang: eng
text: 'This paper characterizes the latency of the simplified successive-cancellation
(SSC) decoding scheme for polar codes under hardware resource constraints. In
particular, when the number of processing elements P that can perform SSC decoding
operations in parallel is limited, as is the case in practice, the latency of
SSC decoding is O(N1-1/μ + N/P log2 log2 N/P), where N is the block length of
the code and μ is the scaling exponent of the channel. Three direct consequences
of this bound are presented. First, in a fully-parallel implementation where P
= N/2, the latency of SSC decoding is O(N1-1/μ), which is sublinear in the block
length. This recovers a result from our earlier work. Second, in a fully-serial
implementation where P = 1, the latency of SSC decoding scales as O(N log2 log2
N). The multiplicative constant is also calculated: we show that the latency of
SSC decoding when P = 1 is given by (2 + o(1))N log2 log2 N. Third, in a semi-parallel
implementation, the smallest P that gives the same latency as that of the fully-parallel
implementation is P = N1/μ. The tightness of our bound on SSC decoding latency
and the applicability of the foregoing results is validated through extensive
simulations.'
acknowledgement: "S. A. Hashemi is supported by a Postdoctoral Fellowship from the
Natural Sciences and\r\nEngineering Research Council of Canada (NSERC) and by Huawei.
M. Mondelli is partially\r\nsupported by the 2019 Lopez-Loreta Prize. A. Fazeli
and A. Vardy were supported in part by\r\nthe National Science Foundation under
Grant CCF-1764104."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Seyyed Ali
full_name: Hashemi, Seyyed Ali
last_name: Hashemi
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
- first_name: Arman
full_name: Fazeli, Arman
last_name: Fazeli
- first_name: Alexander
full_name: Vardy, Alexander
last_name: Vardy
- first_name: John
full_name: Cioffi, John
last_name: Cioffi
- first_name: Andrea
full_name: Goldsmith, Andrea
last_name: Goldsmith
citation:
ama: Hashemi SA, Mondelli M, Fazeli A, Vardy A, Cioffi J, Goldsmith A. Parallelism
versus latency in simplified successive-cancellation decoding of polar codes.
IEEE Transactions on Wireless Communications. 2022;21(6):3909-3920. doi:10.1109/TWC.2021.3125626
apa: Hashemi, S. A., Mondelli, M., Fazeli, A., Vardy, A., Cioffi, J., & Goldsmith,
A. (2022). Parallelism versus latency in simplified successive-cancellation decoding
of polar codes. IEEE Transactions on Wireless Communications. IEEE. https://doi.org/10.1109/TWC.2021.3125626
chicago: Hashemi, Seyyed Ali, Marco Mondelli, Arman Fazeli, Alexander Vardy, John
Cioffi, and Andrea Goldsmith. “Parallelism versus Latency in Simplified Successive-Cancellation
Decoding of Polar Codes.” IEEE Transactions on Wireless Communications.
IEEE, 2022. https://doi.org/10.1109/TWC.2021.3125626.
ieee: S. A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, and A. Goldsmith,
“Parallelism versus latency in simplified successive-cancellation decoding of
polar codes,” IEEE Transactions on Wireless Communications, vol. 21, no.
6. IEEE, pp. 3909–3920, 2022.
ista: Hashemi SA, Mondelli M, Fazeli A, Vardy A, Cioffi J, Goldsmith A. 2022. Parallelism
versus latency in simplified successive-cancellation decoding of polar codes.
IEEE Transactions on Wireless Communications. 21(6), 3909–3920.
mla: Hashemi, Seyyed Ali, et al. “Parallelism versus Latency in Simplified Successive-Cancellation
Decoding of Polar Codes.” IEEE Transactions on Wireless Communications,
vol. 21, no. 6, IEEE, 2022, pp. 3909–20, doi:10.1109/TWC.2021.3125626.
short: S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith,
IEEE Transactions on Wireless Communications 21 (2022) 3909–3920.
date_created: 2021-11-28T23:01:29Z
date_published: 2022-06-01T00:00:00Z
date_updated: 2026-08-12T06:43:01Z
day: '01'
department:
- _id: MaMo
doi: 10.1109/TWC.2021.3125626
external_id:
arxiv:
- '2012.13378'
isi:
- '000809406400028'
intvolume: ' 21'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2012.13378
month: '06'
oa: 1
oa_version: Preprint
page: 3909-3920
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: IEEE Transactions on Wireless Communications
publication_identifier:
eissn:
- 1558-2248
issn:
- 1536-1276
publication_status: published
publisher: IEEE
quality_controlled: '1'
related_material:
record:
- id: '10053'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Parallelism versus latency in simplified successive-cancellation decoding of
polar codes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 21
year: '2022'
...