[{"ddc":["570"],"publication_identifier":{"eissn":["2050-084X"]},"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"author":[{"last_name":"Tomanek","orcid":"0000-0001-6197-363X","first_name":"Isabella","full_name":"Tomanek, Isabella","id":"3981F020-F248-11E8-B48F-1D18A9856A87"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet","first_name":"Calin C"}],"day":"22","related_material":{"record":[{"id":"12339","status":"public","relation":"research_data"}],"link":[{"url":"https://doi.org/10.5281/zenodo.6974122","relation":"software"}]},"pmid":1,"publication_status":"published","year":"2022","intvolume":"        11","article_number":"e82240","corr_author":"1","file_date_updated":"2023-01-23T08:56:21Z","scopus_import":"1","publication":"eLife","article_processing_charge":"No","external_id":{"isi":["000912674700001"],"pmid":["36546673"]},"file":[{"date_updated":"2023-01-23T08:56:21Z","date_created":"2023-01-23T08:56:21Z","file_name":"2022_eLife_Tomanek.pdf","creator":"dernst","file_id":"12338","access_level":"open_access","success":1,"file_size":8835954,"checksum":"9321fd5f06ff59d5e2d33daee84b3da1","content_type":"application/pdf","relation":"main_file"}],"license":"https://creativecommons.org/licenses/by/4.0/","has_accepted_license":"1","date_published":"2022-12-22T00:00:00Z","quality_controlled":"1","department":[{"_id":"CaGu"}],"publisher":"eLife Sciences Publications","abstract":[{"text":"Together, copy-number and point mutations form the basis for most evolutionary novelty, through the process of gene duplication and divergence. While a plethora of genomic data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic reporter system that can distinguish between copy-number and point mutations, we study their early and transient adaptive dynamics in real time in Escherichia coli. We find two qualitatively different routes of adaptation, depending on the level of functional improvement needed. In conditions of high gene expression demand, the two mutation types occur as a combination. However, under low gene expression demand, copy-number and point mutations are mutually exclusive; here, owing to their higher frequency, adaptation is dominated by copy-number mutations, in a process we term amplification hindrance. Ultimately, due to high reversal rates and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation, but also constrain sequence divergence over evolutionary time scales.","lang":"eng"}],"citation":{"mla":"Tomanek, Isabella, and Calin C. Guet. “Adaptation Dynamics between Copynumber and Point Mutations.” <i>ELife</i>, vol. 11, e82240, eLife Sciences Publications, 2022, doi:<a href=\"https://doi.org/10.7554/ELIFE.82240\">10.7554/ELIFE.82240</a>.","ieee":"I. Tomanek and C. C. Guet, “Adaptation dynamics between copynumber and point mutations,” <i>eLife</i>, vol. 11. eLife Sciences Publications, 2022.","apa":"Tomanek, I., &#38; Guet, C. C. (2022). Adaptation dynamics between copynumber and point mutations. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/ELIFE.82240\">https://doi.org/10.7554/ELIFE.82240</a>","short":"I. Tomanek, C.C. Guet, ELife 11 (2022).","chicago":"Tomanek, Isabella, and Calin C Guet. “Adaptation Dynamics between Copynumber and Point Mutations.” <i>ELife</i>. eLife Sciences Publications, 2022. <a href=\"https://doi.org/10.7554/ELIFE.82240\">https://doi.org/10.7554/ELIFE.82240</a>.","ama":"Tomanek I, Guet CC. Adaptation dynamics between copynumber and point mutations. <i>eLife</i>. 2022;11. doi:<a href=\"https://doi.org/10.7554/ELIFE.82240\">10.7554/ELIFE.82240</a>","ista":"Tomanek I, Guet CC. 2022. Adaptation dynamics between copynumber and point mutations. eLife. 11, e82240."},"title":"Adaptation dynamics between copynumber and point mutations","type":"journal_article","isi":1,"status":"public","doi":"10.7554/ELIFE.82240","_id":"12333","volume":11,"date_updated":"2025-03-06T14:03:50Z","date_created":"2023-01-22T23:00:55Z","article_type":"original","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"acknowledgement":"We are grateful to N Barton, F Kondrashov, M Lagator, M Pleska, R Roemhild, D Siekhaus, and G\r\nTkacik for input on the manuscript and to K Tomasek for help with flow cytometry.","oa_version":"Published Version","month":"12"},{"status":"public","_id":"12339","doi":"10.5061/dryad.rfj6q57ds","year":"2022","date_updated":"2025-03-06T14:03:50Z","date_created":"2023-01-23T09:00:37Z","corr_author":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"oa_version":"Published Version","month":"12","article_processing_charge":"No","date_published":"2022-12-23T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5061/dryad.rfj6q57ds"}],"ddc":["570"],"department":[{"_id":"CaGu"}],"publisher":"Dryad","abstract":[{"text":"Copy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in Escherichia coli. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also constrain sequence divergence over evolutionary time scales.","lang":"eng"}],"citation":{"ista":"Tomanek I, Guet CC. 2022. Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose, Dryad, <a href=\"https://doi.org/10.5061/dryad.rfj6q57ds\">10.5061/dryad.rfj6q57ds</a>.","ama":"Tomanek I, Guet CC. Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose. 2022. doi:<a href=\"https://doi.org/10.5061/dryad.rfj6q57ds\">10.5061/dryad.rfj6q57ds</a>","chicago":"Tomanek, Isabella, and Calin C Guet. “Flow Cytometry YFP and CFP Data and Deep Sequencing Data of Populations Evolving in Galactose.” Dryad, 2022. <a href=\"https://doi.org/10.5061/dryad.rfj6q57ds\">https://doi.org/10.5061/dryad.rfj6q57ds</a>.","ieee":"I. Tomanek and C. C. Guet, “Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose.” Dryad, 2022.","apa":"Tomanek, I., &#38; Guet, C. C. (2022). Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose. Dryad. <a href=\"https://doi.org/10.5061/dryad.rfj6q57ds\">https://doi.org/10.5061/dryad.rfj6q57ds</a>","short":"I. Tomanek, C.C. Guet, (2022).","mla":"Tomanek, Isabella, and Calin C. Guet. <i>Flow Cytometry YFP and CFP Data and Deep Sequencing Data of Populations Evolving in Galactose</i>. Dryad, 2022, doi:<a href=\"https://doi.org/10.5061/dryad.rfj6q57ds\">10.5061/dryad.rfj6q57ds</a>."},"author":[{"first_name":"Isabella","orcid":"0000-0001-6197-363X","last_name":"Tomanek","id":"3981F020-F248-11E8-B48F-1D18A9856A87","full_name":"Tomanek, Isabella"},{"orcid":"0000-0001-6220-2052","last_name":"Guet","first_name":"Calin C","full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"}],"title":"Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose","day":"23","type":"research_data_reference","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"12333"}]}},{"isi":1,"status":"public","doi":"10.1109/FOCS54457.2022.00091","_id":"12432","volume":"2022-October","date_updated":"2025-07-10T11:50:26Z","date_created":"2023-01-29T23:00:59Z","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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","oa_version":"None","month":"12","page":"919-930","date_published":"2022-12-01T00:00:00Z","quality_controlled":"1","department":[{"_id":"MaKw"}],"publisher":"Institute of Electrical and Electronics Engineers","abstract":[{"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.","lang":"eng"}],"conference":{"location":"Denver, CO, United States","start_date":"2022-10-31","name":"FOCS: Foundations of Computer Science","end_date":"2022-11-03"},"citation":{"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.","ama":"Anastos M. Solving the Hamilton cycle problem fast on average. In: <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>. Vol 2022-October. Institute of Electrical and Electronics Engineers; 2022:919-930. doi:<a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">10.1109/FOCS54457.2022.00091</a>","chicago":"Anastos, Michael. “Solving the Hamilton Cycle Problem Fast on Average.” In <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>, 2022–October:919–30. Institute of Electrical and Electronics Engineers, 2022. <a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">https://doi.org/10.1109/FOCS54457.2022.00091</a>.","short":"M. Anastos, in:, 63rd Annual IEEE Symposium on Foundations of Computer Science, Institute of Electrical and Electronics Engineers, 2022, pp. 919–930.","ieee":"M. Anastos, “Solving the Hamilton cycle problem fast on average,” in <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>, Denver, CO, United States, 2022, vol. 2022–October, pp. 919–930.","apa":"Anastos, M. (2022). Solving the Hamilton cycle problem fast on average. In <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i> (Vol. 2022–October, pp. 919–930). Denver, CO, United States: Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">https://doi.org/10.1109/FOCS54457.2022.00091</a>","mla":"Anastos, Michael. “Solving the Hamilton Cycle Problem Fast on Average.” <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>, vol. 2022–October, Institute of Electrical and Electronics Engineers, 2022, pp. 919–30, doi:<a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">10.1109/FOCS54457.2022.00091</a>."},"title":"Solving the Hamilton cycle problem fast on average","type":"conference","year":"2022","publication_status":"published","corr_author":"1","scopus_import":"1","publication":"63rd Annual IEEE Symposium on Foundations of Computer Science","external_id":{"isi":["000909382900084"]},"article_processing_charge":"No","project":[{"call_identifier":"H2020","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program"}],"publication_identifier":{"issn":["0272-5428"],"isbn":["9781665455190"]},"ec_funded":1,"author":[{"last_name":"Anastos","first_name":"Michael","full_name":"Anastos, Michael","id":"0b2a4358-bb35-11ec-b7b9-e3279b593dbb"}],"day":"01"},{"ddc":["000"],"author":[{"first_name":"Pramod","last_name":"Rao","full_name":"Rao, Pramod"},{"first_name":"Mallikarjun","last_name":"B R","full_name":"B R, Mallikarjun"},{"first_name":"Gereon","last_name":"Fox","full_name":"Fox, Gereon"},{"full_name":"Weyrich, Tim","last_name":"Weyrich","first_name":"Tim"},{"id":"49876194-F248-11E8-B48F-1D18A9856A87","full_name":"Bickel, Bernd","first_name":"Bernd","orcid":"0000-0001-6511-9385","last_name":"Bickel"},{"last_name":"Seidel","first_name":"Hans-Peter","full_name":"Seidel, Hans-Peter"},{"full_name":"Pfister, Hanspeter","last_name":"Pfister","first_name":"Hanspeter"},{"first_name":"Wojciech","last_name":"Matusik","full_name":"Matusik, Wojciech"},{"full_name":"Tewari, Ayush","last_name":"Tewari","first_name":"Ayush"},{"last_name":"Theobalt","first_name":"Christian","full_name":"Theobalt, Christian"},{"first_name":"Mohamed","last_name":"Elgharib","full_name":"Elgharib, Mohamed"}],"day":"01","year":"2022","publication_status":"published","article_number":"708","file_date_updated":"2023-01-30T10:48:37Z","scopus_import":"1","publication":"33rd British Machine Vision Conference","article_processing_charge":"No","file":[{"checksum":"b60b70bb48700aee709c85a69231821d","file_size":5202710,"relation":"main_file","content_type":"application/pdf","title":"VoRF: Volumetric Relightable Faces","creator":"bbickel","file_name":"vorf_main.pdf","date_created":"2023-01-30T10:48:18Z","date_updated":"2023-01-30T10:48:18Z","access_level":"open_access","file_id":"12453"},{"title":"VoRF: Volumetric Relightable Faces – SUPPLEMENTAL MATERIAL –","content_type":"application/pdf","relation":"supplementary_material","file_size":37953188,"checksum":"ce5f4ce66eaaa1590ee5df989fca6f61","file_id":"12454","access_level":"open_access","date_updated":"2023-01-30T10:48:29Z","date_created":"2023-01-30T10:48:29Z","file_name":"vorf_supp.pdf","creator":"bbickel"},{"file_size":57855492,"checksum":"08aecca434b08fee75ee1efe87943718","content_type":"video/mp4","relation":"supplementary_material","date_created":"2023-01-30T10:48:37Z","date_updated":"2023-01-30T10:48:37Z","creator":"bbickel","file_name":"video.mp4","file_id":"12455","access_level":"open_access"}],"main_file_link":[{"open_access":"1","url":"https://bmvc2022.mpi-inf.mpg.de/708/"}],"date_published":"2022-12-01T00:00:00Z","has_accepted_license":"1","department":[{"_id":"BeBi"}],"quality_controlled":"1","abstract":[{"lang":"eng","text":"Portrait viewpoint and illumination editing is an important problem with several applications in VR/AR, movies, and photography. Comprehensive knowledge of geometry and illumination is critical for obtaining photorealistic results. Current methods are unable to explicitly model in 3D while handing both viewpoint and illumination editing from a single image. In this paper, we propose VoRF, a novel approach that can take even a single portrait image as input and relight human heads under novel illuminations that can be viewed from arbitrary viewpoints. VoRF represents a human head as a continuous volumetric field and learns a prior model of human heads using a coordinate-based MLP with separate latent spaces for identity and illumination. The prior model is learnt in an auto-decoder manner over a diverse class of head shapes and appearances, allowing VoRF to generalize to novel test identities from a single input image. Additionally, VoRF has a reflectance MLP that uses the intermediate features of the prior model for rendering One-Light-at-A-Time (OLAT) images under novel views. We synthesize novel illuminations by combining these OLAT images with target environment maps. Qualitative and quantitative evaluations demonstrate the effectiveness of VoRF for relighting and novel view synthesis even when applied to unseen subjects under uncontrolled illuminations."}],"publisher":"British Machine Vision Association and Society for Pattern Recognition","conference":{"start_date":"2022-11-21","location":"London, United Kingdom","name":"BMVC: British Machine Vision Conference","end_date":"2022-11-24"},"citation":{"chicago":"Rao, Pramod, Mallikarjun B R, Gereon Fox, Tim Weyrich, Bernd Bickel, Hans-Peter Seidel, Hanspeter Pfister, et al. “VoRF: Volumetric Relightable Faces.” In <i>33rd British Machine Vision Conference</i>. British Machine Vision Association and Society for Pattern Recognition, 2022.","short":"P. Rao, M. B R, G. Fox, T. Weyrich, B. Bickel, H.-P. Seidel, H. Pfister, W. Matusik, A. Tewari, C. Theobalt, M. Elgharib, in:, 33rd British Machine Vision Conference, British Machine Vision Association and Society for Pattern Recognition, 2022.","apa":"Rao, P., B R, M., Fox, G., Weyrich, T., Bickel, B., Seidel, H.-P., … Elgharib, M. (2022). VoRF: Volumetric Relightable Faces. In <i>33rd British Machine Vision Conference</i>. London, United Kingdom: British Machine Vision Association and Society for Pattern Recognition.","ieee":"P. Rao <i>et al.</i>, “VoRF: Volumetric Relightable Faces,” in <i>33rd British Machine Vision Conference</i>, London, United Kingdom, 2022.","mla":"Rao, Pramod, et al. “VoRF: Volumetric Relightable Faces.” <i>33rd British Machine Vision Conference</i>, 708, British Machine Vision Association and Society for Pattern Recognition, 2022.","ista":"Rao P, B R M, Fox G, Weyrich T, Bickel B, Seidel H-P, Pfister H, Matusik W, Tewari A, Theobalt C, Elgharib M. 2022. VoRF: Volumetric Relightable Faces. 33rd British Machine Vision Conference. BMVC: British Machine Vision Conference, 708.","ama":"Rao P, B R M, Fox G, et al. VoRF: Volumetric Relightable Faces. In: <i>33rd British Machine Vision Conference</i>. British Machine Vision Association and Society for Pattern Recognition; 2022."},"type":"conference","title":"VoRF: Volumetric Relightable Faces","_id":"12452","status":"public","date_created":"2023-01-30T10:47:06Z","date_updated":"2023-10-31T08:40:55Z","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"oa_version":"Published Version","acknowledgement":"This work was supported by the ERC Consolidator Grant 4DReply (770784).","month":"12"},{"issue":"11","oa_version":"Published Version","acknowledgement":"The authors would like to thank Andrea Montanari for helpful discussions.\r\nM Mondelli was partially supported by the 2019 Lopez-Loreta Prize. R Venkataramanan was partially supported by the Alan Turing Institute under the EPSRC Grant\r\nEP/N510129/1.","month":"11","doi":"10.1088/1742-5468/ac9828","_id":"12480","status":"public","isi":1,"date_created":"2023-02-02T08:31:57Z","date_updated":"2025-04-15T07:50:16Z","volume":2022,"keyword":["Statistics","Probability and Uncertainty","Statistics and Probability","Statistical and Nonlinear Physics"],"article_type":"original","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","oa":1,"language":[{"iso":"eng"}],"citation":{"ama":"Mondelli M, Venkataramanan R. Approximate message passing with spectral initialization for generalized linear models. <i>Journal of Statistical Mechanics: Theory and Experiment</i>. 2022;2022(11). doi:<a href=\"https://doi.org/10.1088/1742-5468/ac9828\">10.1088/1742-5468/ac9828</a>","ista":"Mondelli M, Venkataramanan R. 2022. Approximate message passing with spectral initialization for generalized linear models. Journal of Statistical Mechanics: Theory and Experiment. 2022(11), 114003.","apa":"Mondelli, M., &#38; Venkataramanan, R. (2022). Approximate message passing with spectral initialization for generalized linear models. <i>Journal of Statistical Mechanics: Theory and Experiment</i>. IOP Publishing. <a href=\"https://doi.org/10.1088/1742-5468/ac9828\">https://doi.org/10.1088/1742-5468/ac9828</a>","ieee":"M. Mondelli and R. Venkataramanan, “Approximate message passing with spectral initialization for generalized linear models,” <i>Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2022, no. 11. IOP Publishing, 2022.","short":"M. Mondelli, R. Venkataramanan, Journal of Statistical Mechanics: Theory and Experiment 2022 (2022).","mla":"Mondelli, Marco, and Ramji Venkataramanan. “Approximate Message Passing with Spectral Initialization for Generalized Linear Models.” <i>Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2022, no. 11, 114003, IOP Publishing, 2022, doi:<a href=\"https://doi.org/10.1088/1742-5468/ac9828\">10.1088/1742-5468/ac9828</a>.","chicago":"Mondelli, Marco, and Ramji Venkataramanan. “Approximate Message Passing with Spectral Initialization for Generalized Linear Models.” <i>Journal of Statistical Mechanics: Theory and Experiment</i>. IOP Publishing, 2022. <a href=\"https://doi.org/10.1088/1742-5468/ac9828\">https://doi.org/10.1088/1742-5468/ac9828</a>."},"type":"journal_article","title":"Approximate message passing with spectral initialization for generalized linear models","date_published":"2022-11-24T00:00:00Z","has_accepted_license":"1","department":[{"_id":"MaMo"}],"quality_controlled":"1","abstract":[{"text":"We consider the problem of estimating a signal from measurements obtained via a generalized linear model. We focus on estimators based on approximate message passing (AMP), a family of iterative algorithms with many appealing features: the performance of AMP in the high-dimensional limit can be succinctly characterized under suitable model assumptions; AMP can also be tailored to the empirical distribution of the signal entries, and for a wide class of estimation problems, AMP is conjectured to be optimal among all polynomial-time algorithms. However, a major issue of AMP is that in many models (such as phase retrieval), it requires an initialization correlated with the ground-truth signal and independent from the measurement matrix. Assuming that such an initialization is available is typically not realistic. In this paper, we solve this problem by proposing an AMP algorithm initialized with a spectral estimator. With such an initialization, the standard AMP analysis fails since the spectral estimator depends in a complicated way on the design matrix. Our main contribution is a rigorous characterization of the performance of AMP with spectral initialization in the high-dimensional limit. The key technical idea is to define and analyze a two-phase artificial AMP algorithm that first produces the spectral estimator, and then closely approximates the iterates of the true AMP. We also provide numerical results that demonstrate the validity of the proposed approach.","lang":"eng"}],"publisher":"IOP Publishing","scopus_import":"1","publication":"Journal of Statistical Mechanics: Theory and Experiment","external_id":{"isi":["000889589900001"]},"article_processing_charge":"Yes (via OA deal)","file":[{"relation":"main_file","content_type":"application/pdf","checksum":"01411ffa76d3e380a0446baeb89b1ef7","success":1,"file_size":1729997,"access_level":"open_access","file_id":"12481","creator":"dernst","file_name":"2022_JourStatisticalMechanics_Mondelli.pdf","date_updated":"2023-02-02T08:35:52Z","date_created":"2023-02-02T08:35:52Z"}],"year":"2022","publication_status":"published","intvolume":"      2022","corr_author":"1","article_number":"114003","file_date_updated":"2023-02-02T08:35:52Z","author":[{"first_name":"Marco","orcid":"0000-0002-3242-7020","last_name":"Mondelli","full_name":"Mondelli, Marco","id":"27EB676C-8706-11E9-9510-7717E6697425"},{"full_name":"Venkataramanan, Ramji","first_name":"Ramji","last_name":"Venkataramanan"}],"day":"24","related_material":{"record":[{"relation":"earlier_version","status":"public","id":"10598"}]},"publication_identifier":{"issn":["1742-5468"]},"project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"ddc":["510","530"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"}},{"ddc":["000"],"project":[{"name":"Vienna Graduate School on Computational Optimization","_id":"9B9290DE-BA93-11EA-9121-9846C619BF3A","grant_number":"W1260-N35"}],"publication_identifier":{"issn":["2835-8856"]},"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"day":"22","related_material":{"link":[{"url":"https://github.com/ISTAustria-CVML/FLEA","relation":"software","description":"source code"}]},"author":[{"first_name":"Eugenia B","orcid":"0000-0002-7778-3221","last_name":"Iofinova","id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","full_name":"Iofinova, Eugenia B"},{"full_name":"Konstantinov, Nikola H","id":"4B9D76E4-F248-11E8-B48F-1D18A9856A87","last_name":"Konstantinov","orcid":"0009-0009-5204-7621","first_name":"Nikola H"},{"id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph","first_name":"Christoph","orcid":"0000-0001-8622-7887","last_name":"Lampert"}],"year":"2022","publication_status":"published","file_date_updated":"2023-02-23T10:30:04Z","acknowledged_ssus":[{"_id":"ScienComp"}],"corr_author":"1","publication":"Transactions on Machine Learning Research","file":[{"creator":"dernst","file_name":"2022_TMLR_Iofinova.pdf","date_created":"2023-02-23T10:30:04Z","date_updated":"2023-02-23T10:30:04Z","access_level":"open_access","file_id":"12673","checksum":"97c8a8470759cab597abb973ca137a3b","file_size":1948063,"success":1,"relation":"main_file","content_type":"application/pdf"}],"article_processing_charge":"No","external_id":{"arxiv":["2106.11732"]},"quality_controlled":"1","department":[{"_id":"ChLa"}],"has_accepted_license":"1","main_file_link":[{"url":"https://openreview.net/forum?id=XsPopigZXV","open_access":"1"}],"date_published":"2022-12-22T00:00:00Z","publisher":"ML Research Press","abstract":[{"lang":"eng","text":"Fairness-aware learning aims at constructing classifiers that not only make accurate predictions, but also do not discriminate against specific groups. It is a fast-growing area of\r\nmachine learning with far-reaching societal impact. However, existing fair learning methods\r\nare vulnerable to accidental or malicious artifacts in the training data, which can cause\r\nthem to unknowingly produce unfair classifiers. In this work we address the problem of\r\nfair learning from unreliable training data in the robust multisource setting, where the\r\navailable training data comes from multiple sources, a fraction of which might not be representative of the true data distribution. We introduce FLEA, a filtering-based algorithm\r\nthat identifies and suppresses those data sources that would have a negative impact on\r\nfairness or accuracy if they were used for training. As such, FLEA is not a replacement of\r\nprior fairness-aware learning methods but rather an augmentation that makes any of them\r\nrobust against unreliable training data. We show the effectiveness of our approach by a\r\ndiverse range of experiments on multiple datasets. Additionally, we prove formally that\r\n–given enough data– FLEA protects the learner against corruptions as long as the fraction of\r\naffected data sources is less than half. Our source code and documentation are available at\r\nhttps://github.com/ISTAustria-CVML/FLEA."}],"arxiv":1,"citation":{"ista":"Iofinova EB, Konstantinov NH, Lampert C. 2022. FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research.","ama":"Iofinova EB, Konstantinov NH, Lampert C. FLEA: Provably robust fair multisource learning from unreliable training data. <i>Transactions on Machine Learning Research</i>. 2022.","chicago":"Iofinova, Eugenia B, Nikola H Konstantinov, and Christoph Lampert. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” <i>Transactions on Machine Learning Research</i>. ML Research Press, 2022.","ieee":"E. B. Iofinova, N. H. Konstantinov, and C. Lampert, “FLEA: Provably robust fair multisource learning from unreliable training data,” <i>Transactions on Machine Learning Research</i>. ML Research Press, 2022.","apa":"Iofinova, E. B., Konstantinov, N. H., &#38; Lampert, C. (2022). FLEA: Provably robust fair multisource learning from unreliable training data. <i>Transactions on Machine Learning Research</i>. ML Research Press.","short":"E.B. Iofinova, N.H. Konstantinov, C. Lampert, Transactions on Machine Learning Research (2022).","mla":"Iofinova, Eugenia B., et al. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” <i>Transactions on Machine Learning Research</i>, ML Research Press, 2022."},"title":"FLEA: Provably robust fair multisource learning from unreliable training data","type":"journal_article","date_updated":"2025-12-30T11:04:31Z","date_created":"2023-02-02T20:29:57Z","status":"public","_id":"12495","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"article_type":"original","oa_version":"Published Version","acknowledgement":"The authors would like to thank Bernd Prach, Elias Frantar, Alexandra Peste, Mahdi Nikdan, and Peter Súkeník for their helpful feedback. This research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific Computing (SciComp). This publication was made possible by an ETH AI Center postdoctoral fellowship granted to Nikola Konstantinov. Eugenia Iofinova was supported in part by the FWF DK VGSCO, grant agreement number W1260-N35. ","month":"12"},{"publication":"33rd International Conference on Concurrency Theory","scopus_import":"1","file":[{"relation":"main_file","content_type":"application/pdf","checksum":"9e97e15628f66b2ad77f535bb0327dee","success":1,"file_size":717940,"access_level":"open_access","file_id":"12520","file_name":"2022_LIPICs_Henzinger2.pdf","creator":"dernst","date_updated":"2023-02-06T09:21:09Z","date_created":"2023-02-06T09:21:09Z"}],"article_processing_charge":"No","intvolume":"       243","year":"2022","publication_status":"published","file_date_updated":"2023-02-06T09:21:09Z","corr_author":"1","related_material":{"record":[{"relation":"later_version","status":"public","id":"18530"}]},"day":"06","author":[{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A","first_name":"Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger"},{"full_name":"Lehtinen, Karoliina","last_name":"Lehtinen","first_name":"Karoliina"},{"full_name":"Totzke, Patrick","last_name":"Totzke","first_name":"Patrick"}],"project":[{"name":"Vigilant Algorithmic Monitoring of Software","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020","grant_number":"101020093"}],"publication_identifier":{"isbn":["9783959772464"],"issn":["1868-8969"]},"ddc":["000"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"ec_funded":1,"oa_version":"Published Version","acknowledgement":"Thomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nPatrick Totzke: acknowledges support from the EPSRC, project no. EP/V025848/1.\r\n","page":"14:1-14:21","month":"09","date_created":"2023-02-05T17:24:23Z","date_updated":"2025-09-08T14:35:16Z","volume":243,"_id":"12508","doi":"10.4230/LIPIcs.CONCUR.2022.14","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"language":[{"iso":"eng"}],"citation":{"ieee":"T. A. Henzinger, K. Lehtinen, and P. Totzke, “History-deterministic timed automata,” in <i>33rd International Conference on Concurrency Theory</i>, Warsaw, Poland, 2022, vol. 243, p. 14:1-14:21.","apa":"Henzinger, T. A., Lehtinen, K., &#38; Totzke, P. (2022). History-deterministic timed automata. In <i>33rd International Conference on Concurrency Theory</i> (Vol. 243, p. 14:1-14:21). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.14\">https://doi.org/10.4230/LIPIcs.CONCUR.2022.14</a>","short":"T.A. Henzinger, K. Lehtinen, P. Totzke, in:, 33rd International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21.","mla":"Henzinger, Thomas A., et al. “History-Deterministic Timed Automata.” <i>33rd International Conference on Concurrency Theory</i>, vol. 243, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21, doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.14\">10.4230/LIPIcs.CONCUR.2022.14</a>.","chicago":"Henzinger, Thomas A, Karoliina Lehtinen, and Patrick Totzke. “History-Deterministic Timed Automata.” In <i>33rd International Conference on Concurrency Theory</i>, 243:14:1-14:21. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.14\">https://doi.org/10.4230/LIPIcs.CONCUR.2022.14</a>.","ama":"Henzinger TA, Lehtinen K, Totzke P. History-deterministic timed automata. In: <i>33rd International Conference on Concurrency Theory</i>. Vol 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:14:1-14:21. doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2022.14\">10.4230/LIPIcs.CONCUR.2022.14</a>","ista":"Henzinger TA, Lehtinen K, Totzke P. 2022. History-deterministic timed automata. 33rd International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 243, 14:1-14:21."},"conference":{"name":"CONCUR: Conference on Concurrency Theory","end_date":"2022-09-16","location":"Warsaw, Poland","start_date":"2022-09-13"},"type":"conference","title":"History-deterministic timed automata","department":[{"_id":"ToHe"}],"quality_controlled":"1","date_published":"2022-09-06T00:00:00Z","has_accepted_license":"1","abstract":[{"lang":"eng","text":"We explore the notion of history-determinism in the context of timed automata (TA). History-deterministic automata are those in which nondeterminism can be resolved on the fly, based on the run constructed thus far. History-determinism is a robust property that admits different game-based characterisations, and history-deterministic specifications allow for game-based verification without an expensive determinization step.\r\nWe show yet another characterisation of history-determinism in terms of fair simulation, at the general level of labelled transition systems: a system is history-deterministic precisely if and only if it fairly simulates all language smaller systems.\r\nFor timed automata over infinite timed words it is known that universality is undecidable for Büchi TA. We show that for history-deterministic TA with arbitrary parity acceptance, timed universality, inclusion, and synthesis all remain decidable and are ExpTime-complete.\r\nFor the subclass of TA with safety or reachability acceptance, we show that checking whether such an automaton is history-deterministic is decidable (in ExpTime), and history-deterministic TA with safety acceptance are effectively determinizable without introducing new automata states."}],"publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","alternative_title":["LIPIcs"]},{"quality_controlled":"1","department":[{"_id":"ToHe"}],"has_accepted_license":"1","date_published":"2022-08-22T00:00:00Z","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","abstract":[{"lang":"eng","text":"A graph game is a two-player zero-sum game in which the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. In bidding games, both players have budgets, and in each turn, we hold an \"auction\" (bidding) to determine which player moves the token. In this survey, we consider several bidding mechanisms and their effect on the properties of the game. Specifically, bidding games, and in particular bidding games of infinite duration, have an intriguing equivalence with random-turn games in which in each turn, the player who moves is chosen randomly. We summarize how minor changes in the bidding mechanism lead to unexpected differences in the equivalence with random-turn games."}],"citation":{"mla":"Avni, Guy, and Thomas A. Henzinger. “An Updated Survey of Bidding Games on Graphs.” <i>47th International Symposium on Mathematical Foundations of Computer Science</i>, vol. 241, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 3:1-3:6, doi:<a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">10.4230/LIPIcs.MFCS.2022.3</a>.","apa":"Avni, G., &#38; Henzinger, T. A. (2022). An updated survey of bidding games on graphs. In <i>47th International Symposium on Mathematical Foundations of Computer Science</i> (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>","short":"G. Avni, T.A. Henzinger, in:, 47th International Symposium on Mathematical Foundations of Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 2022, p. 3:1-3:6.","ieee":"G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,” in <i>47th International Symposium on Mathematical Foundations of Computer Science</i>, Vienna, Austria, 2022, vol. 241, p. 3:1-3:6.","chicago":"Avni, Guy, and Thomas A Henzinger. “An Updated Survey of Bidding Games on Graphs.” In <i>47th International Symposium on Mathematical Foundations of Computer Science</i>, 241:3:1-3:6. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>.","ama":"Avni G, Henzinger TA. An updated survey of bidding games on graphs. In: <i>47th International Symposium on Mathematical Foundations of Computer Science</i>. Vol 241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:<a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">10.4230/LIPIcs.MFCS.2022.3</a>","ista":"Avni G, Henzinger TA. 2022. An updated survey of bidding games on graphs. 47th International Symposium on Mathematical Foundations of Computer Science. MFCS: Mathematical Foundations of Computer ScienceLeibniz International Proceedings in Informatics (LIPIcs) vol. 241, 3:1-3:6."},"conference":{"start_date":"2022-08-22","location":"Vienna, Austria","name":"MFCS: Mathematical Foundations of Computer Science","end_date":"2022-08-26"},"title":"An updated survey of bidding games on graphs","type":"conference","place":"Dagstuhl, Germany","date_updated":"2025-07-10T11:50:27Z","volume":241,"date_created":"2023-02-05T17:26:01Z","status":"public","_id":"12509","doi":"10.4230/LIPIcs.MFCS.2022.3","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"acknowledgement":"Guy Avni: Work partially supported by the Israel Science Foundation, ISF grant agreement\r\nno 1679/21.\r\nThomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nWe would like to thank all our collaborators Milad Aghajohari, Ventsislav Chonev, Rasmus Ibsen-Jensen, Ismäel Jecker, Petr Novotný, Josef Tkadlec, and Ðorđe Žikelić; we hope the collaboration was as fun and meaningful for you as it was for us.","oa_version":"Published Version","page":"3:1-3:6","month":"08","ddc":["000"],"publication_identifier":{"issn":["1868-8969"],"isbn":["9783959772563"]},"project":[{"grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software"}],"ec_funded":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"series_title":"Leibniz International Proceedings in Informatics (LIPIcs)","day":"22","author":[{"full_name":"Avni, Guy","id":"463C8BC2-F248-11E8-B48F-1D18A9856A87","first_name":"Guy","orcid":"0000-0001-5588-8287","last_name":"Avni"},{"last_name":"Henzinger","orcid":"0000-0002-2985-7724","first_name":"Thomas A","full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"}],"intvolume":"       241","year":"2022","publication_status":"published","file_date_updated":"2023-02-06T09:13:04Z","corr_author":"1","publication":"47th International Symposium on Mathematical Foundations of Computer Science","scopus_import":"1","file":[{"content_type":"application/pdf","relation":"main_file","file_size":624586,"success":1,"checksum":"1888ec9421622f9526fbec2de035f132","file_id":"12519","access_level":"open_access","date_created":"2023-02-06T09:13:04Z","date_updated":"2023-02-06T09:13:04Z","file_name":"2022_LIPICs_Avni.pdf","creator":"dernst"}],"article_processing_charge":"No"},{"type":"journal_article","title":"GoTube: Scalable statistical verification of continuous-depth models","citation":{"ama":"Gruenbacher SA, Lechner M, Hasani R, et al. GoTube: Scalable statistical verification of continuous-depth models. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. 2022;36(6):6755-6764. doi:<a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">10.1609/aaai.v36i6.20631</a>","ista":"Gruenbacher SA, Lechner M, Hasani R, Rus D, Henzinger TA, Smolka SA, Grosu R. 2022. GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. 36(6), 6755–6764.","mla":"Gruenbacher, Sophie A., et al. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 6, Association for the Advancement of Artificial Intelligence, 2022, pp. 6755–64, doi:<a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">10.1609/aaai.v36i6.20631</a>.","short":"S.A. Gruenbacher, M. Lechner, R. Hasani, D. Rus, T.A. Henzinger, S.A. Smolka, R. Grosu, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022) 6755–6764.","ieee":"S. A. Gruenbacher <i>et al.</i>, “GoTube: Scalable statistical verification of continuous-depth models,” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 6. Association for the Advancement of Artificial Intelligence, pp. 6755–6764, 2022.","apa":"Gruenbacher, S. A., Lechner, M., Hasani, R., Rus, D., Henzinger, T. A., Smolka, S. A., &#38; Grosu, R. (2022). GoTube: Scalable statistical verification of continuous-depth models. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">https://doi.org/10.1609/aaai.v36i6.20631</a>","chicago":"Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association for the Advancement of Artificial Intelligence, 2022. <a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">https://doi.org/10.1609/aaai.v36i6.20631</a>."},"arxiv":1,"abstract":[{"lang":"eng","text":"We introduce a new statistical verification algorithm that formally quantifies the behavioral robustness of any time-continuous process formulated as a continuous-depth model. Our algorithm solves a set of global optimization (Go) problems over a given time horizon to construct a tight enclosure (Tube) of the set of all process executions starting from a ball of initial states. We call our algorithm GoTube. Through its construction, GoTube ensures that the bounding tube is conservative up to a desired probability and up to a desired tightness.\r\n GoTube is implemented in JAX and optimized to scale to complex continuous-depth neural network models. Compared to advanced reachability analysis tools for time-continuous neural networks, GoTube does not accumulate overapproximation errors between time steps and avoids the infamous wrapping effect inherent in symbolic techniques. We show that GoTube substantially outperforms state-of-the-art verification tools in terms of the size of the initial ball, speed, time-horizon, task completion, and scalability on a large set of experiments.\r\n GoTube is stable and sets the state-of-the-art in terms of its ability to scale to time horizons well beyond what has been previously possible."}],"publisher":"Association for the Advancement of Artificial Intelligence","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2107.08467"}],"date_published":"2022-06-28T00:00:00Z","department":[{"_id":"ToHe"}],"quality_controlled":"1","month":"06","page":"6755-6764","issue":"6","acknowledgement":"SG is funded by the Austrian Science Fund (FWF) project number W1255-N23. ML and TH are supported in part by FWF under grant Z211-N23 (Wittgenstein Award) and the ERC-2020-AdG 101020093. SS is supported by NSF awards DCL-2040599, CCF-1918225, and CPS-1446832. RH and DR are partially supported by Boeing. RG is partially supported by Horizon-2020 ECSEL Project grant No. 783163 (iDev40).","oa_version":"Preprint","keyword":["General Medicine"],"article_type":"original","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"doi":"10.1609/aaai.v36i6.20631","_id":"12510","status":"public","date_created":"2023-02-05T17:27:42Z","date_updated":"2025-04-15T06:26:14Z","volume":36,"author":[{"first_name":"Sophie A.","last_name":"Gruenbacher","full_name":"Gruenbacher, Sophie A."},{"full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","first_name":"Mathias"},{"last_name":"Hasani","first_name":"Ramin","full_name":"Hasani, Ramin"},{"full_name":"Rus, Daniela","last_name":"Rus","first_name":"Daniela"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger","first_name":"Thomas A"},{"full_name":"Smolka, Scott A.","last_name":"Smolka","first_name":"Scott A."},{"full_name":"Grosu, Radu","last_name":"Grosu","first_name":"Radu"}],"day":"28","ec_funded":1,"project":[{"call_identifier":"FWF","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","name":"Formal methods for the design and analysis of complex systems"},{"call_identifier":"H2020","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","grant_number":"101020093","name":"Vigilant Algorithmic Monitoring of Software"}],"publication_identifier":{"issn":["2159-5399"],"isbn":["978577358350"],"eissn":["2374-3468"]},"article_processing_charge":"No","external_id":{"arxiv":["2107.08467"]},"scopus_import":"1","publication":"Proceedings of the AAAI Conference on Artificial Intelligence","publication_status":"published","year":"2022","intvolume":"        36"},{"corr_author":"1","publication_status":"published","year":"2022","intvolume":"     13748","external_id":{"isi":["000921318200020"]},"article_processing_charge":"No","scopus_import":"1","publication":"Theory of Cryptography","publication_identifier":{"isbn":["9783031223648"],"eissn":["1611-3349"],"issn":["0302-9743"]},"author":[{"full_name":"Bogdanov, Andrej","last_name":"Bogdanov","first_name":"Andrej"},{"last_name":"Cueto Noval","orcid":"0000-0002-2505-4246","first_name":"Miguel","id":"ffc563a3-f6e0-11ea-865d-e3cce03d17cc","full_name":"Cueto Noval, Miguel"},{"last_name":"Hoffmann","orcid":"0000-0003-2027-5549","first_name":"Charlotte","id":"0f78d746-dc7d-11ea-9b2f-83f92091afe7","full_name":"Hoffmann, Charlotte"},{"full_name":"Rosen, Alon","first_name":"Alon","last_name":"Rosen"}],"day":"21","language":[{"iso":"eng"}],"oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","status":"public","isi":1,"doi":"10.1007/978-3-031-22365-5_20","_id":"12516","date_updated":"2024-10-09T21:04:05Z","volume":13748,"date_created":"2023-02-05T23:01:00Z","month":"12","page":"565-592","acknowledgement":"We are grateful to Devika Sharma and Luca Trevisan for their insight and advice and to an anonymous reviewer for helpful comments.\r\n\r\nThis work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101019547). The first author was additionally supported by RGC GRF CUHK14209920 and the fourth author was additionally supported by ISF grant No. 1399/17, project PROMETHEUS (Grant 780701), and Cariplo CRYPTONOMEX grant.","oa_version":"Preprint","alternative_title":["LNCS"],"publisher":"Springer Nature","abstract":[{"text":"The homogeneous continuous LWE (hCLWE) problem is to distinguish samples of a specific high-dimensional Gaussian mixture from standard normal samples. It was shown to be at least as hard as Learning with Errors, but no reduction in the other direction is currently known.\r\nWe present four new public-key encryption schemes based on the hardness of hCLWE, with varying tradeoffs between decryption and security errors, and different discretization techniques. Our schemes yield a polynomial-time algorithm for solving hCLWE using a Statistical Zero-Knowledge oracle.","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://eprint.iacr.org/2022/093"}],"date_published":"2022-12-21T00:00:00Z","quality_controlled":"1","department":[{"_id":"KrPi"}],"title":"Public-Key Encryption from Homogeneous CLWE","type":"conference","conference":{"location":"Chicago, IL, United States","start_date":"2022-11-07","end_date":"2022-11-10","name":"TCC: Theory of Cryptography"},"citation":{"short":"A. Bogdanov, M. Cueto Noval, C. Hoffmann, A. Rosen, in:, Theory of Cryptography, Springer Nature, 2022, pp. 565–592.","ieee":"A. Bogdanov, M. Cueto Noval, C. Hoffmann, and A. Rosen, “Public-Key Encryption from Homogeneous CLWE,” in <i>Theory of Cryptography</i>, Chicago, IL, United States, 2022, vol. 13748, pp. 565–592.","mla":"Bogdanov, Andrej, et al. “Public-Key Encryption from Homogeneous CLWE.” <i>Theory of Cryptography</i>, vol. 13748, Springer Nature, 2022, pp. 565–92, doi:<a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">10.1007/978-3-031-22365-5_20</a>.","apa":"Bogdanov, A., Cueto Noval, M., Hoffmann, C., &#38; Rosen, A. (2022). Public-Key Encryption from Homogeneous CLWE. In <i>Theory of Cryptography</i> (Vol. 13748, pp. 565–592). Chicago, IL, United States: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">https://doi.org/10.1007/978-3-031-22365-5_20</a>","chicago":"Bogdanov, Andrej, Miguel Cueto Noval, Charlotte Hoffmann, and Alon Rosen. “Public-Key Encryption from Homogeneous CLWE.” In <i>Theory of Cryptography</i>, 13748:565–92. Springer Nature, 2022. <a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">https://doi.org/10.1007/978-3-031-22365-5_20</a>.","ama":"Bogdanov A, Cueto Noval M, Hoffmann C, Rosen A. Public-Key Encryption from Homogeneous CLWE. In: <i>Theory of Cryptography</i>. Vol 13748. Springer Nature; 2022:565-592. doi:<a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">10.1007/978-3-031-22365-5_20</a>","ista":"Bogdanov A, Cueto Noval M, Hoffmann C, Rosen A. 2022. Public-Key Encryption from Homogeneous CLWE. Theory of Cryptography. TCC: Theory of Cryptography, LNCS, vol. 13748, 565–592."}},{"quality_controlled":"1","date_published":"2022-03-29T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/978-3-030-99527-0_5"}],"publisher":"Springer Nature","abstract":[{"lang":"eng","text":"We consider turn-based stochastic 2-player games on graphs with ω-regular winning conditions. We provide a direct symbolic algorithm for solving such games when the winning condition is formulated as a Rabin condition. For a stochastic Rabin game with k pairs over a game graph with n vertices, our algorithm runs in O(nk+2k!) symbolic steps, which improves the state of the art.\r\nWe have implemented our symbolic algorithm, along with performance optimizations including parallellization and acceleration, in a BDD-based synthesis tool called Fairsyn. We demonstrate the superiority of Fairsyn compared to the state of the art on a set of synthetic benchmarks derived from the VLTS benchmark suite and on a control system benchmark from the literature. In our experiments, Fairsyn performed significantly faster with up to two orders of magnitude improvement in computation time."}],"alternative_title":["LNCS"],"citation":{"chicago":"Banerjee, Tamajit, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck, and Sadegh Soudjani. “A Direct Symbolic Algorithm for Solving Stochastic Rabin Games.” In <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, 13244:81–98. Springer Nature, 2022. <a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">https://doi.org/10.1007/978-3-030-99527-0_5</a>.","ieee":"T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, and S. Soudjani, “A direct symbolic algorithm for solving stochastic rabin games,” in <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, Munich, Germany, 2022, vol. 13244, pp. 81–98.","apa":"Banerjee, T., Majumdar, R., Mallik, K., Schmuck, A.-K., &#38; Soudjani, S. (2022). A direct symbolic algorithm for solving stochastic rabin games. In <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i> (Vol. 13244, pp. 81–98). Munich, Germany: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">https://doi.org/10.1007/978-3-030-99527-0_5</a>","mla":"Banerjee, Tamajit, et al. “A Direct Symbolic Algorithm for Solving Stochastic Rabin Games.” <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, vol. 13244, Springer Nature, 2022, pp. 81–98, doi:<a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">10.1007/978-3-030-99527-0_5</a>.","short":"T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, S. Soudjani, in:, 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2022, pp. 81–98.","ista":"Banerjee T, Majumdar R, Mallik K, Schmuck A-K, Soudjani S. 2022. A direct symbolic algorithm for solving stochastic rabin games. 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13244, 81–98.","ama":"Banerjee T, Majumdar R, Mallik K, Schmuck A-K, Soudjani S. A direct symbolic algorithm for solving stochastic rabin games. In: <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>. Vol 13244. Springer Nature; 2022:81-98. doi:<a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">10.1007/978-3-030-99527-0_5</a>"},"conference":{"start_date":"2022-04-02","location":"Munich, Germany","end_date":"2022-04-07","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems"},"title":"A direct symbolic algorithm for solving stochastic rabin games","type":"conference","volume":13244,"date_updated":"2024-10-09T21:04:10Z","date_created":"2023-02-08T11:43:34Z","status":"public","extern":"1","_id":"12529","doi":"10.1007/978-3-030-99527-0_5","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"oa_version":"Published Version","page":"81-98","month":"03","publication_identifier":{"eisbn":["9783030995270"]},"day":"29","author":[{"full_name":"Banerjee, Tamajit","last_name":"Banerjee","first_name":"Tamajit"},{"last_name":"Majumdar","first_name":"Rupak","full_name":"Majumdar, Rupak"},{"orcid":"0000-0001-9864-7475","last_name":"Mallik","first_name":"Kaushik","id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","full_name":"Mallik, Kaushik"},{"full_name":"Schmuck, Anne-Kathrin","last_name":"Schmuck","first_name":"Anne-Kathrin"},{"full_name":"Soudjani, Sadegh","first_name":"Sadegh","last_name":"Soudjani"}],"intvolume":"     13244","year":"2022","publication_status":"published","corr_author":"1","publication":"28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems","scopus_import":"1","article_processing_charge":"No"},{"page":"24:1-24:11","article_processing_charge":"No","month":"05","publication":"25th ACM International Conference on Hybrid Systems: Computation and Control","oa_version":"None","scopus_import":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"date_created":"2023-02-08T11:43:50Z","date_updated":"2023-02-09T08:53:13Z","publication_status":"published","_id":"12530","year":"2022","doi":"10.1145/3501710.3519535","extern":"1","status":"public","type":"conference","day":"01","title":"BOCoSy: Small but powerful symbolic output-feedback control","author":[{"full_name":"Finkbeiner, Bernd","last_name":"Finkbeiner","first_name":"Bernd"},{"first_name":"Kaushik","orcid":"0000-0001-9864-7475","last_name":"Mallik","id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","full_name":"Mallik, Kaushik"},{"full_name":"Passing, Noemi","first_name":"Noemi","last_name":"Passing"},{"full_name":"Schledjewski, Malte","last_name":"Schledjewski","first_name":"Malte"},{"full_name":"Schmuck, Anne-Kathrin","first_name":"Anne-Kathrin","last_name":"Schmuck"}],"citation":{"ista":"Finkbeiner B, Mallik K, Passing N, Schledjewski M, Schmuck A-K. 2022. BOCoSy: Small but powerful symbolic output-feedback control. 25th ACM International Conference on Hybrid Systems: Computation and Control. HSCC: International Conference on Hybrid Systems Computation and Control, 24:1-24:11.","ama":"Finkbeiner B, Mallik K, Passing N, Schledjewski M, Schmuck A-K. BOCoSy: Small but powerful symbolic output-feedback control. In: <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>. ACM; 2022:24:1-24:11. doi:<a href=\"https://doi.org/10.1145/3501710.3519535\">10.1145/3501710.3519535</a>","chicago":"Finkbeiner, Bernd, Kaushik Mallik, Noemi Passing, Malte Schledjewski, and Anne-Kathrin Schmuck. “BOCoSy: Small but Powerful Symbolic Output-Feedback Control.” In <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>, 24:1-24:11. ACM, 2022. <a href=\"https://doi.org/10.1145/3501710.3519535\">https://doi.org/10.1145/3501710.3519535</a>.","apa":"Finkbeiner, B., Mallik, K., Passing, N., Schledjewski, M., &#38; Schmuck, A.-K. (2022). BOCoSy: Small but powerful symbolic output-feedback control. In <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i> (p. 24:1-24:11). Milan, Italy: ACM. <a href=\"https://doi.org/10.1145/3501710.3519535\">https://doi.org/10.1145/3501710.3519535</a>","ieee":"B. Finkbeiner, K. Mallik, N. Passing, M. Schledjewski, and A.-K. Schmuck, “BOCoSy: Small but powerful symbolic output-feedback control,” in <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>, Milan, Italy, 2022, p. 24:1-24:11.","short":"B. Finkbeiner, K. Mallik, N. Passing, M. Schledjewski, A.-K. Schmuck, in:, 25th ACM International Conference on Hybrid Systems: Computation and Control, ACM, 2022, p. 24:1-24:11.","mla":"Finkbeiner, Bernd, et al. “BOCoSy: Small but Powerful Symbolic Output-Feedback Control.” <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>, ACM, 2022, p. 24:1-24:11, doi:<a href=\"https://doi.org/10.1145/3501710.3519535\">10.1145/3501710.3519535</a>."},"conference":{"location":"Milan, Italy","start_date":"2022-05-04","end_date":"2022-05-06","name":"HSCC: International Conference on Hybrid Systems Computation and Control"},"abstract":[{"text":"We present BOCoSy, a tool for Bounded symbolic Output-feedback Controller Synthesis. Given a specification, BOCoSy synthesizes symbolic output-feedback controllers which interact with a given plant via a pre-defined finite symbolic interface. BOCoSy solves this problem by a new lazy abstraction-refinement technique which starts with a very coarse abstraction of the external trace semantics of the given plant and iteratively removes non-admissible behavior from this abstract model until a controller is found. BOCoSy steers the search for controllers towards small and concise state space representations by utilizing ideas from bounded synthesis. As a result, BOCoSy returns small and explainable controllers that are still powerful enough to solve the given synthesis problem. We show that BOCoSy is able to synthesize small, human readable symbolic controllers quickly on a set of benchmarks.","lang":"eng"}],"publisher":"ACM","publication_identifier":{"isbn":["9781450391962"]},"quality_controlled":"1","date_published":"2022-05-01T00:00:00Z"},{"citation":{"ista":"Barbier J, Hou T, Mondelli M, Saenz M. 2022. The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation? 36th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, NeurIPS, vol. 35.","ama":"Barbier J, Hou T, Mondelli M, Saenz M. The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation? In: <i>36th Annual Conference on Neural Information Processing Systems</i>. Vol 35. ; 2022.","chicago":"Barbier, Jean, TianQi Hou, Marco Mondelli, and Manuel Saenz. “The Price of Ignorance: How Much Does It Cost to Forget Noise Structure in Low-Rank Matrix Estimation?” In <i>36th Annual Conference on Neural Information Processing Systems</i>, Vol. 35, 2022.","apa":"Barbier, J., Hou, T., Mondelli, M., &#38; Saenz, M. (2022). The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation? In <i>36th Annual Conference on Neural Information Processing Systems</i> (Vol. 35). New Orleans, LA, United States.","ieee":"J. Barbier, T. Hou, M. Mondelli, and M. Saenz, “The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation?,” in <i>36th Annual Conference on Neural Information Processing Systems</i>, New Orleans, LA, United States, 2022, vol. 35.","short":"J. Barbier, T. Hou, M. Mondelli, M. Saenz, in:, 36th Annual Conference on Neural Information Processing Systems, 2022.","mla":"Barbier, Jean, et al. “The Price of Ignorance: How Much Does It Cost to Forget Noise Structure in Low-Rank Matrix Estimation?” <i>36th Annual Conference on Neural Information Processing Systems</i>, vol. 35, 2022."},"arxiv":1,"conference":{"location":"New Orleans, LA, United States","start_date":"2022-11-28","end_date":"2022-12-09","name":"NeurIPS: Neural Information Processing Systems"},"type":"conference","title":"The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation?","department":[{"_id":"MaMo"}],"quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2205.10009"}],"date_published":"2022-11-20T00:00:00Z","abstract":[{"lang":"eng","text":"We consider the problem of estimating a rank-1 signal corrupted by structured rotationally invariant noise, and address the following question: how well do inference algorithms perform when the noise statistics is unknown and hence Gaussian noise is assumed? While the matched Bayes-optimal setting with unstructured noise is well understood, the analysis of this mismatched problem is only at its premises. In this paper, we make a step towards understanding the effect of the strong source of mismatch which is the noise statistics. Our main technical contribution is the rigorous analysis of a Bayes estimator and of an approximate message passing (AMP) algorithm, both of which incorrectly assume a Gaussian setup. The first result exploits the theory of spherical integrals and of low-rank matrix perturbations; the idea behind the second one is to design and analyze an artificial AMP which, by taking advantage of the flexibility in the denoisers, is able to \"correct\" the mismatch. Armed with these sharp asymptotic characterizations, we unveil a rich and often unexpected phenomenology. For example, despite AMP is in principle designed to efficiently compute the Bayes estimator, the former is outperformed by the latter in terms of mean-square error. We show that this performance gap is due to an incorrect estimation of the signal norm. In fact, when the SNR is large enough, the overlaps of the AMP and the Bayes estimator coincide, and they even match those of optimal estimators taking into account the structure of the noise."}],"alternative_title":["NeurIPS"],"acknowledgement":"M. Mondelli was partially supported by the 2019 Lopez-Loreta Prize. The authors acknowledge\r\ndiscussions with A. Krajenbrink, M. Robinson, A. Depope, N. Macris and F. Pourkamali.\r\n","oa_version":"Preprint","month":"11","date_created":"2023-02-10T13:45:41Z","date_updated":"2024-10-09T21:04:25Z","volume":35,"_id":"12536","status":"public","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"day":"20","author":[{"first_name":"Jean","last_name":"Barbier","full_name":"Barbier, Jean"},{"first_name":"TianQi","last_name":"Hou","full_name":"Hou, TianQi"},{"full_name":"Mondelli, Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","first_name":"Marco","last_name":"Mondelli","orcid":"0000-0002-3242-7020"},{"full_name":"Saenz, Manuel","first_name":"Manuel","last_name":"Saenz"}],"publication_identifier":{"isbn":["9781713871088"]},"publication":"36th Annual Conference on Neural Information Processing Systems","scopus_import":"1","external_id":{"arxiv":["2205.10009"]},"article_processing_charge":"No","intvolume":"        35","year":"2022","publication_status":"published","corr_author":"1"},{"publication_identifier":{"eissn":["1049-5258"],"isbn":["9781713871088"]},"project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"author":[{"full_name":"Bombari, Simone","id":"ca726dda-de17-11ea-bc14-f9da834f63aa","first_name":"Simone","last_name":"Bombari"},{"full_name":"Amani, Mohammad Hossein","first_name":"Mohammad Hossein","last_name":"Amani"},{"orcid":"0000-0002-3242-7020","last_name":"Mondelli","first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco"}],"day":"24","publication_status":"published","year":"2022","intvolume":"        35","corr_author":"1","OA_type":"green","publication":"36th Conference on Neural Information Processing Systems","article_processing_charge":"No","external_id":{"arxiv":["2205.10217"]},"main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2205.10217"}],"date_published":"2022-07-24T00:00:00Z","department":[{"_id":"MaMo"}],"quality_controlled":"1","alternative_title":["Advances in Neural Information Processing Systems"],"abstract":[{"text":"The Neural Tangent Kernel (NTK) has emerged as a powerful tool to provide memorization, optimization and generalization guarantees in deep neural networks. A line of work has studied the NTK spectrum for two-layer and deep networks with at least a layer with Ω(N) neurons, N being the number of training samples. Furthermore, there is increasing evidence suggesting that deep networks with sub-linear layer widths are powerful memorizers and optimizers, as long as the number of parameters exceeds the number of samples. Thus, a natural open question is whether the NTK is well conditioned in such a challenging sub-linear setup. In this paper, we answer this question in the affirmative. Our key technical contribution is a lower bound on the smallest NTK eigenvalue for deep networks with the minimum possible over-parameterization: the number of parameters is roughly Ω(N) and, hence, the number of neurons is as little as Ω(N−−√). To showcase the applicability of our NTK bounds, we provide two results concerning memorization capacity and optimization guarantees for gradient descent training.","lang":"eng"}],"publisher":"Neural Information Processing Systems Foundation","conference":{"end_date":"2022-12-09","name":"NeurIPS: Neural Information Processing Systems","start_date":"2022-11-28","location":"New Orleans, LA, United States"},"OA_place":"repository","citation":{"ama":"Bombari S, Amani MH, Mondelli M. Memorization and optimization in deep neural networks with minimum over-parameterization. In: <i>36th Conference on Neural Information Processing Systems</i>. Vol 35. Neural Information Processing Systems Foundation; 2022:7628-7640.","ista":"Bombari S, Amani MH, Mondelli M. 2022. Memorization and optimization in deep neural networks with minimum over-parameterization. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 7628–7640.","ieee":"S. Bombari, M. H. Amani, and M. Mondelli, “Memorization and optimization in deep neural networks with minimum over-parameterization,” in <i>36th Conference on Neural Information Processing Systems</i>, New Orleans, LA, United States, 2022, vol. 35, pp. 7628–7640.","apa":"Bombari, S., Amani, M. H., &#38; Mondelli, M. (2022). Memorization and optimization in deep neural networks with minimum over-parameterization. In <i>36th Conference on Neural Information Processing Systems</i> (Vol. 35, pp. 7628–7640). New Orleans, LA, United States: Neural Information Processing Systems Foundation.","mla":"Bombari, Simone, et al. “Memorization and Optimization in Deep Neural Networks with Minimum Over-Parameterization.” <i>36th Conference on Neural Information Processing Systems</i>, vol. 35, Neural Information Processing Systems Foundation, 2022, pp. 7628–40.","short":"S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 7628–7640.","chicago":"Bombari, Simone, Mohammad Hossein Amani, and Marco Mondelli. “Memorization and Optimization in Deep Neural Networks with Minimum Over-Parameterization.” In <i>36th Conference on Neural Information Processing Systems</i>, 35:7628–40. Neural Information Processing Systems Foundation, 2022."},"arxiv":1,"type":"conference","title":"Memorization and optimization in deep neural networks with minimum over-parameterization","_id":"12537","status":"public","date_created":"2023-02-10T13:46:37Z","date_updated":"2025-05-14T11:28:22Z","volume":35,"oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"oa_version":"Preprint","acknowledgement":"The authors were partially supported by the 2019 Lopez-Loreta prize, and they would like to thank\r\nQuynh Nguyen, Mahdi Soltanolkotabi and Adel Javanmard for helpful discussions.\r\n","month":"07","page":"7628-7640"},{"article_processing_charge":"No","external_id":{"isi":["000904341100099"],"arxiv":["2205.08199"]},"publication":"IEEE Information Theory Workshop","scopus_import":"1","publication_status":"published","year":"2022","day":"16","author":[{"first_name":"Mohammad Hossein","last_name":"Amani","full_name":"Amani, Mohammad Hossein"},{"last_name":"Bombari","first_name":"Simone","full_name":"Bombari, Simone","id":"ca726dda-de17-11ea-bc14-f9da834f63aa"},{"id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco","last_name":"Mondelli","orcid":"0000-0002-3242-7020","first_name":"Marco"},{"full_name":"Pukdee, Rattana","last_name":"Pukdee","first_name":"Rattana"},{"full_name":"Rini, Stefano","first_name":"Stefano","last_name":"Rini"}],"publication_identifier":{"isbn":["9781665483414"]},"page":"588-593","month":"11","oa_version":"Preprint","language":[{"iso":"eng"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","oa":1,"article_type":"original","date_updated":"2025-09-10T09:53:31Z","date_created":"2023-02-10T13:47:56Z","isi":1,"status":"public","doi":"10.1109/ITW54588.2022.9965870","_id":"12538","title":"Sharp asymptotics on the compression of two-layer neural networks","type":"journal_article","arxiv":1,"citation":{"ista":"Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. 2022. Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop., 588–593.","ama":"Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>. 2022:588-593. doi:<a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">10.1109/ITW54588.2022.9965870</a>","chicago":"Amani, Mohammad Hossein, Simone Bombari, Marco Mondelli, Rattana Pukdee, and Stefano Rini. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.” <i>IEEE Information Theory Workshop</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">https://doi.org/10.1109/ITW54588.2022.9965870</a>.","mla":"Amani, Mohammad Hossein, et al. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.” <i>IEEE Information Theory Workshop</i>, IEEE, 2022, pp. 588–93, doi:<a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">10.1109/ITW54588.2022.9965870</a>.","short":"M.H. Amani, S. Bombari, M. Mondelli, R. Pukdee, S. Rini, IEEE Information Theory Workshop (2022) 588–593.","ieee":"M. H. Amani, S. Bombari, M. Mondelli, R. Pukdee, and S. Rini, “Sharp asymptotics on the compression of two-layer neural networks,” <i>IEEE Information Theory Workshop</i>. IEEE, pp. 588–593, 2022.","apa":"Amani, M. H., Bombari, S., Mondelli, M., Pukdee, R., &#38; Rini, S. (2022). Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>. Mumbai, India: IEEE. <a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">https://doi.org/10.1109/ITW54588.2022.9965870</a>"},"conference":{"end_date":"2022-11-09","name":"ITW: Information Theory Workshop","location":"Mumbai, India","start_date":"2022-11-01"},"publisher":"IEEE","abstract":[{"text":"In this paper, we study the compression of a target two-layer neural network with N nodes into a compressed network with M<N nodes. More precisely, we consider the setting in which the weights of the target network are i.i.d. sub-Gaussian, and we minimize the population L_2 loss between the outputs of the target and of the compressed network, under the assumption of Gaussian inputs. By using tools from high-dimensional probability, we show that this non-convex problem can be simplified when the target network is sufficiently over-parameterized, and provide the error rate of this approximation as a function of the input dimension and N. In this mean-field limit, the simplified objective, as well as the optimal weights of the compressed network, does not depend on the realization of the target network, but only on expected scaling factors. Furthermore, for networks with ReLU activation, we conjecture that the optimum of the simplified optimization problem is achieved by taking weights on the Equiangular Tight Frame (ETF), while the scaling of the weights and the orientation of the ETF depend on the parameters of the target network. Numerical evidence is provided to support this conjecture.","lang":"eng"}],"quality_controlled":"1","department":[{"_id":"MaMo"}],"date_published":"2022-11-16T00:00:00Z","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2205.08199"}]},{"ddc":["000"],"project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"author":[{"full_name":"Venkataramanan, Ramji","last_name":"Venkataramanan","first_name":"Ramji"},{"last_name":"Kögler","first_name":"Kevin","full_name":"Kögler, Kevin","id":"94ec913c-dc85-11ea-9058-e5051ab2428b"},{"first_name":"Marco","last_name":"Mondelli","orcid":"0000-0002-3242-7020","full_name":"Mondelli, Marco","id":"27EB676C-8706-11E9-9510-7717E6697425"}],"file_date_updated":"2023-02-13T10:53:11Z","article_number":"22","corr_author":"1","intvolume":"       162","publication_status":"published","year":"2022","file":[{"date_updated":"2023-02-13T10:53:11Z","date_created":"2023-02-13T10:53:11Z","file_name":"2022_PMLR_Venkataramanan.pdf","creator":"dernst","file_id":"12547","access_level":"open_access","success":1,"file_size":2341343,"checksum":"67436eb0a660789514cdf9db79e84683","content_type":"application/pdf","relation":"main_file"}],"article_processing_charge":"No","publication":"Proceedings of the 39th International Conference on Machine Learning","publisher":"ML Research Press","abstract":[{"lang":"eng","text":"We consider the problem of signal estimation in generalized linear models defined via rotationally invariant design matrices. Since these matrices can have an arbitrary spectral distribution, this model is well suited for capturing complex correlation structures which often arise in applications. We propose a novel family of approximate message passing (AMP) algorithms for signal estimation, and rigorously characterize their performance in the high-dimensional limit via a state evolution recursion. Our rotationally invariant AMP has complexity of the same order as the existing AMP derived under the restrictive assumption of a Gaussian design; our algorithm also recovers this existing AMP as a special case. Numerical results showcase a performance close to Vector AMP (which is conjectured to be Bayes-optimal in some settings), but obtained with a much lower complexity, as the proposed algorithm does not require a computationally expensive singular value decomposition."}],"quality_controlled":"1","department":[{"_id":"MaMo"}],"has_accepted_license":"1","date_published":"2022-01-01T00:00:00Z","title":"Estimation in rotationally invariant generalized linear models via approximate message passing","type":"conference","citation":{"chicago":"Venkataramanan, Ramji, Kevin Kögler, and Marco Mondelli. “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.” In <i>Proceedings of the 39th International Conference on Machine Learning</i>, Vol. 162. ML Research Press, 2022.","apa":"Venkataramanan, R., Kögler, K., &#38; Mondelli, M. (2022). Estimation in rotationally invariant generalized linear models via approximate message passing. In <i>Proceedings of the 39th International Conference on Machine Learning</i> (Vol. 162). Baltimore, MD, United States: ML Research Press.","mla":"Venkataramanan, Ramji, et al. “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.” <i>Proceedings of the 39th International Conference on Machine Learning</i>, vol. 162, 22, ML Research Press, 2022.","short":"R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022.","ieee":"R. Venkataramanan, K. Kögler, and M. Mondelli, “Estimation in rotationally invariant generalized linear models via approximate message passing,” in <i>Proceedings of the 39th International Conference on Machine Learning</i>, Baltimore, MD, United States, 2022, vol. 162.","ista":"Venkataramanan R, Kögler K, Mondelli M. 2022. Estimation in rotationally invariant generalized linear models via approximate message passing. Proceedings of the 39th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 162, 22.","ama":"Venkataramanan R, Kögler K, Mondelli M. Estimation in rotationally invariant generalized linear models via approximate message passing. In: <i>Proceedings of the 39th International Conference on Machine Learning</i>. Vol 162. ML Research Press; 2022."},"conference":{"start_date":"2022-07-17","location":"Baltimore, MD, United States","name":"ICML: International Conference on Machine Learning","end_date":"2022-07-23"},"language":[{"iso":"eng"}],"oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":162,"date_updated":"2025-04-15T07:50:16Z","date_created":"2023-02-10T13:49:04Z","status":"public","_id":"12540","oa_version":"Published Version","acknowledgement":"The authors would like to thank the anonymous reviewers for their helpful comments. KK and MM were partially supported by the 2019 Lopez-Loreta Prize."},{"external_id":{"arxiv":["2203.01640"]},"article_processing_charge":"No","scopus_import":"1","publication":"Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022","corr_author":"1","publication_status":"published","year":"2022","intvolume":"        36","author":[{"id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1","full_name":"Meggendorfer, Tobias","orcid":"0000-0002-1712-2165","last_name":"Meggendorfer","first_name":"Tobias"}],"day":"28","publication_identifier":{"eissn":["2374-3468"],"isbn":["1577358767"]},"month":"06","page":"9858-9867","issue":"9","oa_version":"Preprint","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"status":"public","_id":"12568","doi":"10.1609/aaai.v36i9.21222","volume":36,"date_updated":"2024-10-09T21:04:32Z","date_created":"2023-02-19T23:00:56Z","title":"Risk-aware stochastic shortest path","type":"conference","conference":{"location":"Virtual","start_date":"2022-02-22","end_date":"2022-03-01","name":"Conference on Artificial Intelligence"},"arxiv":1,"citation":{"ama":"Meggendorfer T. Risk-aware stochastic shortest path. In: <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>. Vol 36. Association for the Advancement of Artificial Intelligence; 2022:9858-9867. doi:<a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">10.1609/aaai.v36i9.21222</a>","ista":"Meggendorfer T. 2022. Risk-aware stochastic shortest path. Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022. Conference on Artificial Intelligence vol. 36, 9858–9867.","apa":"Meggendorfer, T. (2022). Risk-aware stochastic shortest path. In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i> (Vol. 36, pp. 9858–9867). Virtual: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">https://doi.org/10.1609/aaai.v36i9.21222</a>","ieee":"T. Meggendorfer, “Risk-aware stochastic shortest path,” in <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, Virtual, 2022, vol. 36, no. 9, pp. 9858–9867.","short":"T. Meggendorfer, in:, Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–9867.","mla":"Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, vol. 36, no. 9, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–67, doi:<a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">10.1609/aaai.v36i9.21222</a>.","chicago":"Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, 36:9858–67. Association for the Advancement of Artificial Intelligence, 2022. <a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">https://doi.org/10.1609/aaai.v36i9.21222</a>."},"publisher":"Association for the Advancement of Artificial Intelligence","abstract":[{"lang":"eng","text":"We treat the problem of risk-aware control for stochastic shortest path (SSP) on Markov decision processes (MDP). Typically, expectation is considered for SSP, which however is oblivious to the incurred risk. We present an alternative view, instead optimizing conditional value-at-risk (CVaR), an established risk measure. We treat both Markov chains as well as MDP and introduce, through novel insights, two algorithms, based on linear programming and value iteration, respectively. Both algorithms offer precise and provably correct solutions. Evaluation of our prototype implementation shows that risk-aware control is feasible on several moderately sized models."}],"date_published":"2022-06-28T00:00:00Z","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2203.01640"}],"quality_controlled":"1","department":[{"_id":"KrCh"}]},{"abstract":[{"lang":"eng","text":"Supraglacial debris strongly modulates glacier melt rates and can be decisive for ice dynamics and mountain hydrology. It is ubiquitous in High-Mountain Asia, yet because its thickness and supply rate from local topography are poorly known, our ability to forecast regional glacier change and streamflow is limited. Here we combined remote sensing and numerical modelling to resolve supraglacial debris thickness by altitude for 4689 glaciers in High-Mountain Asia, and debris-supply rate to 4141 of those glaciers. Our results reveal extensively thin supraglacial debris and high spatial variability in both debris thickness and supply rate. Debris-supply rate increases with the temperature and slope of debris-supply slopes regionally, and debris thickness increases as ice flow decreases locally. Our centennial-scale estimates of debris-supply rate are typically an order of magnitude or more lower than millennial-scale estimates of headwall-erosion rate from Beryllium-10 cosmogenic nuclides, potentially reflecting episodic debris supply to the region’s glaciers."}],"publisher":"Springer Nature","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s43247-022-00588-2"}],"date_published":"2022-11-05T00:00:00Z","quality_controlled":"1","type":"journal_article","title":"Supraglacial debris thickness and supply rate in High-Mountain Asia","citation":{"mla":"McCarthy, Michael, et al. “Supraglacial Debris Thickness and Supply Rate in High-Mountain Asia.” <i>Communications Earth &#38; Environment</i>, vol. 3, 269, Springer Nature, 2022, doi:<a href=\"https://doi.org/10.1038/s43247-022-00588-2\">10.1038/s43247-022-00588-2</a>.","short":"M. McCarthy, E. Miles, M. Kneib, P. Buri, S. Fugger, F. Pellicciotti, Communications Earth &#38; Environment 3 (2022).","apa":"McCarthy, M., Miles, E., Kneib, M., Buri, P., Fugger, S., &#38; Pellicciotti, F. (2022). Supraglacial debris thickness and supply rate in High-Mountain Asia. <i>Communications Earth &#38; Environment</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s43247-022-00588-2\">https://doi.org/10.1038/s43247-022-00588-2</a>","ieee":"M. McCarthy, E. Miles, M. Kneib, P. Buri, S. Fugger, and F. Pellicciotti, “Supraglacial debris thickness and supply rate in High-Mountain Asia,” <i>Communications Earth &#38; Environment</i>, vol. 3. Springer Nature, 2022.","chicago":"McCarthy, Michael, Evan Miles, Marin Kneib, Pascal Buri, Stefan Fugger, and Francesca Pellicciotti. “Supraglacial Debris Thickness and Supply Rate in High-Mountain Asia.” <i>Communications Earth &#38; Environment</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s43247-022-00588-2\">https://doi.org/10.1038/s43247-022-00588-2</a>.","ama":"McCarthy M, Miles E, Kneib M, Buri P, Fugger S, Pellicciotti F. Supraglacial debris thickness and supply rate in High-Mountain Asia. <i>Communications Earth &#38; Environment</i>. 2022;3. doi:<a href=\"https://doi.org/10.1038/s43247-022-00588-2\">10.1038/s43247-022-00588-2</a>","ista":"McCarthy M, Miles E, Kneib M, Buri P, Fugger S, Pellicciotti F. 2022. Supraglacial debris thickness and supply rate in High-Mountain Asia. Communications Earth &#38; Environment. 3, 269."},"keyword":["General Earth and Planetary Sciences","General Environmental Science"],"article_type":"original","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"language":[{"iso":"eng"}],"_id":"12573","extern":"1","doi":"10.1038/s43247-022-00588-2","status":"public","date_created":"2023-02-20T08:09:27Z","volume":3,"date_updated":"2023-02-28T14:02:22Z","month":"11","oa_version":"Published Version","publication_identifier":{"issn":["2662-4435"]},"author":[{"last_name":"McCarthy","first_name":"Michael","full_name":"McCarthy, Michael"},{"full_name":"Miles, Evan","last_name":"Miles","first_name":"Evan"},{"last_name":"Kneib","first_name":"Marin","full_name":"Kneib, Marin"},{"last_name":"Buri","first_name":"Pascal","full_name":"Buri, Pascal"},{"last_name":"Fugger","first_name":"Stefan","full_name":"Fugger, Stefan"},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca","first_name":"Francesca","last_name":"Pellicciotti"}],"day":"05","article_number":"269","publication_status":"published","year":"2022","intvolume":"         3","article_processing_charge":"No","scopus_import":"1","publication":"Communications Earth & Environment"},{"publisher":"Copernicus Publications","abstract":[{"lang":"eng","text":"Melt from supraglacial ice cliffs is an important contributor to the mass loss of debris-covered glaciers. However, ice cliff contribution is difficult to quantify as they are highly dynamic features, and the paucity of observations of melt rates and their variability leads to large modelling uncertainties. We quantify monsoon season melt and 3D evolution of four ice cliffs over two debris-covered glaciers in High Mountain Asia (Langtang Glacier, Nepal, and 24K Glacier, China) at very high resolution using terrestrial photogrammetry applied to imagery captured from time-lapse cameras installed on lateral moraines. We derive weekly flow-corrected digital elevation models (DEMs) of the glacier surface with a maximum vertical bias of ±0.2 m for Langtang Glacier and ±0.05 m for 24K Glacier and use change detection to determine distributed melt rates at the surfaces of the ice cliffs throughout the study period. We compare the measured melt patterns with those derived from a 3D energy balance model to derive the contribution of the main energy fluxes. We find that ice cliff melt varies considerably throughout the melt season, with maximum melt rates of 5 to 8 cm d−1, and their average melt rates are 11–14 (Langtang) and 4.5 (24K) times higher than the surrounding debris-covered ice. Our results highlight the influence of redistributed supraglacial debris on cliff melt. At both sites, ice cliff albedo is influenced by the presence of thin debris at the ice cliff surface, which is largely controlled on 24K Glacier by liquid precipitation events that wash away this debris. Slightly thicker or patchy debris reduces melt by 1–3 cm d−1 at all sites. Ultimately, our observations show a strong spatio-temporal variability in cliff area at each site, which is controlled by supraglacial streams and ponds and englacial cavities that promote debris slope destabilisation and the lateral expansion of the cliffs. These findings highlight the need to better represent processes of debris redistribution in ice cliff models, to in turn improve estimates of ice cliff contribution to glacier melt and the long-term geomorphological evolution of debris-covered glacier surfaces."}],"date_published":"2022-11-11T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5194/tc-16-4701-2022"}],"quality_controlled":"1","title":"Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry","type":"journal_article","citation":{"ama":"Kneib M, Miles ES, Buri P, et al. Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry. <i>The Cryosphere</i>. 2022;16(11):4701-4725. doi:<a href=\"https://doi.org/10.5194/tc-16-4701-2022\">10.5194/tc-16-4701-2022</a>","ista":"Kneib M, Miles ES, Buri P, Fugger S, McCarthy M, Shaw TE, Chuanxi Z, Truffer M, Westoby MJ, Yang W, Pellicciotti F. 2022. Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry. The Cryosphere. 16(11), 4701–4725.","ieee":"M. Kneib <i>et al.</i>, “Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry,” <i>The Cryosphere</i>, vol. 16, no. 11. Copernicus Publications, pp. 4701–4725, 2022.","short":"M. Kneib, E.S. Miles, P. Buri, S. Fugger, M. McCarthy, T.E. Shaw, Z. Chuanxi, M. Truffer, M.J. Westoby, W. Yang, F. Pellicciotti, The Cryosphere 16 (2022) 4701–4725.","mla":"Kneib, Marin, et al. “Sub-Seasonal Variability of Supraglacial Ice Cliff Melt Rates and Associated Processes from Time-Lapse Photogrammetry.” <i>The Cryosphere</i>, vol. 16, no. 11, Copernicus Publications, 2022, pp. 4701–25, doi:<a href=\"https://doi.org/10.5194/tc-16-4701-2022\">10.5194/tc-16-4701-2022</a>.","apa":"Kneib, M., Miles, E. S., Buri, P., Fugger, S., McCarthy, M., Shaw, T. E., … Pellicciotti, F. (2022). Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry. <i>The Cryosphere</i>. Copernicus Publications. <a href=\"https://doi.org/10.5194/tc-16-4701-2022\">https://doi.org/10.5194/tc-16-4701-2022</a>","chicago":"Kneib, Marin, Evan S. Miles, Pascal Buri, Stefan Fugger, Michael McCarthy, Thomas E. Shaw, Zhao Chuanxi, et al. “Sub-Seasonal Variability of Supraglacial Ice Cliff Melt Rates and Associated Processes from Time-Lapse Photogrammetry.” <i>The Cryosphere</i>. Copernicus Publications, 2022. <a href=\"https://doi.org/10.5194/tc-16-4701-2022\">https://doi.org/10.5194/tc-16-4701-2022</a>."},"article_type":"original","keyword":["Earth-Surface Processes","Water Science and Technology"],"language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"status":"public","_id":"12574","extern":"1","doi":"10.5194/tc-16-4701-2022","volume":16,"date_updated":"2023-02-28T13:59:22Z","date_created":"2023-02-20T08:09:42Z","month":"11","page":"4701-4725","issue":"11","oa_version":"Published Version","publication_identifier":{"issn":["1994-0424"]},"author":[{"first_name":"Marin","last_name":"Kneib","full_name":"Kneib, Marin"},{"first_name":"Evan S.","last_name":"Miles","full_name":"Miles, Evan S."},{"full_name":"Buri, Pascal","first_name":"Pascal","last_name":"Buri"},{"first_name":"Stefan","last_name":"Fugger","full_name":"Fugger, Stefan"},{"last_name":"McCarthy","first_name":"Michael","full_name":"McCarthy, Michael"},{"first_name":"Thomas E.","last_name":"Shaw","full_name":"Shaw, Thomas E."},{"last_name":"Chuanxi","first_name":"Zhao","full_name":"Chuanxi, Zhao"},{"last_name":"Truffer","first_name":"Martin","full_name":"Truffer, Martin"},{"full_name":"Westoby, Matthew J.","last_name":"Westoby","first_name":"Matthew J."},{"full_name":"Yang, Wei","first_name":"Wei","last_name":"Yang"},{"first_name":"Francesca","last_name":"Pellicciotti","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca"}],"day":"11","year":"2022","publication_status":"published","intvolume":"        16","article_processing_charge":"No","scopus_import":"1","publication":"The Cryosphere"},{"issue":"10","oa_version":"Published Version","month":"10","status":"public","_id":"12575","extern":"1","doi":"10.1029/2022ef002852","date_updated":"2023-02-28T13:55:32Z","volume":10,"date_created":"2023-02-20T08:09:49Z","article_type":"original","keyword":["Earth and Planetary Sciences (miscellaneous)","General Environmental Science"],"language":[{"iso":"eng"}],"oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"apa":"McCarthy, M., Meier, F., Fatichi, S., Stocker, B. D., Shaw, T. E., Miles, E., … Pellicciotti, F. (2022). Glacier contributions to river discharge during the current Chilean megadrought. <i>Earth’s Future</i>. American Geophysical Union. <a href=\"https://doi.org/10.1029/2022ef002852\">https://doi.org/10.1029/2022ef002852</a>","mla":"McCarthy, Michael, et al. “Glacier Contributions to River Discharge during the Current Chilean Megadrought.” <i>Earth’s Future</i>, vol. 10, no. 10, e2022EF002852, American Geophysical Union, 2022, doi:<a href=\"https://doi.org/10.1029/2022ef002852\">10.1029/2022ef002852</a>.","short":"M. McCarthy, F. Meier, S. Fatichi, B.D. Stocker, T.E. Shaw, E. Miles, I. Dussaillant, F. Pellicciotti, Earth’s Future 10 (2022).","ieee":"M. McCarthy <i>et al.</i>, “Glacier contributions to river discharge during the current Chilean megadrought,” <i>Earth’s Future</i>, vol. 10, no. 10. American Geophysical Union, 2022.","chicago":"McCarthy, Michael, Fabienne Meier, Simone Fatichi, Benjamin D. Stocker, Thomas E. Shaw, Evan Miles, Inés Dussaillant, and Francesca Pellicciotti. “Glacier Contributions to River Discharge during the Current Chilean Megadrought.” <i>Earth’s Future</i>. American Geophysical Union, 2022. <a href=\"https://doi.org/10.1029/2022ef002852\">https://doi.org/10.1029/2022ef002852</a>.","ama":"McCarthy M, Meier F, Fatichi S, et al. Glacier contributions to river discharge during the current Chilean megadrought. <i>Earth’s Future</i>. 2022;10(10). doi:<a href=\"https://doi.org/10.1029/2022ef002852\">10.1029/2022ef002852</a>","ista":"McCarthy M, Meier F, Fatichi S, Stocker BD, Shaw TE, Miles E, Dussaillant I, Pellicciotti F. 2022. Glacier contributions to river discharge during the current Chilean megadrought. Earth’s Future. 10(10), e2022EF002852."},"title":"Glacier contributions to river discharge during the current Chilean megadrought","type":"journal_article","main_file_link":[{"url":"https://doi.org/10.1029/2022EF002852","open_access":"1"}],"date_published":"2022-10-01T00:00:00Z","quality_controlled":"1","publisher":"American Geophysical Union","abstract":[{"lang":"eng","text":"The current Chilean megadrought has led to acute water shortages in central Chile since 2010. Glaciers have provided vital fresh water to the region's rivers, but the quantity, timing and sustainability of that provision remain unclear. Here we combine in-situ, remote sensing and climate reanalysis data to show that from 2010 to 2018 during the megadrought, unsustainable imbalance ablation of glaciers (ablation not balanced by new snowfall) strongly buffered the late-summer discharge of the Maipo River, a primary source of water to Santiago. If there had been no glaciers, water availability would have been reduced from December through May, with a 31 ± 19% decrease during March. Our results indicate that while the annual contributions of imbalance ablation to river discharge during the megadrought have been small compared to those from precipitation and sustainable balance ablation, they have nevertheless been a substantial input to a hydrological system that was already experiencing high water stress. The water-equivalent volume of imbalance ablation generated in the Maipo Basin between 2010 and 2018 was 740 × 106 m3 (19 ± 12 mm yr−1), approximately 3.4 times the capacity of the basin's El Yeso Reservoir. This is equivalent to 14% of Santiago's potable water use in that time, while total glacier ablation was equivalent to 59%. We show that glacier retreat will exacerbate river discharge deficits and further jeopardize water availability in central Chile if precipitation deficits endure, and conjecture that these effects will be amplified by climatic warming."}],"scopus_import":"1","publication":"Earth's Future","article_processing_charge":"No","year":"2022","publication_status":"published","intvolume":"        10","article_number":"e2022EF002852","author":[{"first_name":"Michael","last_name":"McCarthy","full_name":"McCarthy, Michael"},{"full_name":"Meier, Fabienne","first_name":"Fabienne","last_name":"Meier"},{"full_name":"Fatichi, Simone","first_name":"Simone","last_name":"Fatichi"},{"last_name":"Stocker","first_name":"Benjamin D.","full_name":"Stocker, Benjamin D."},{"last_name":"Shaw","first_name":"Thomas E.","full_name":"Shaw, Thomas E."},{"first_name":"Evan","last_name":"Miles","full_name":"Miles, Evan"},{"full_name":"Dussaillant, Inés","first_name":"Inés","last_name":"Dussaillant"},{"first_name":"Francesca","last_name":"Pellicciotti","full_name":"Pellicciotti, Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"}],"day":"01","publication_identifier":{"issn":["2328-4277"]}}]