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Elvis Dohmatob
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2020 – today
- 2024
- [c24]Vivien Cabannes, Elvis Dohmatob, Alberto Bietti:
Scaling Laws for Associative Memories. ICLR 2024 - [c23]Elvis Dohmatob:
Consistent Adversarially Robust Linear Classification: Non-Parametric Setting. ICML 2024 - [c22]Elvis Dohmatob, Yunzhen Feng, Pu Yang, François Charton, Julia Kempe:
A Tale of Tails: Model Collapse as a Change of Scaling Laws. ICML 2024 - [c21]Elvis Dohmatob, Meyer Scetbon:
Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms. ICML 2024 - [i29]Elvis Dohmatob, Yunzhen Feng, Pu Yang, François Charton, Julia Kempe:
A Tale of Tails: Model Collapse as a Change of Scaling Laws. CoRR abs/2402.07043 (2024) - [i28]Elvis Dohmatob, Yunzhen Feng, Julia Kempe:
Model Collapse Demystified: The Case of Regression. CoRR abs/2402.07712 (2024) - [i27]Yunzhen Feng, Elvis Dohmatob, Pu Yang, François Charton, Julia Kempe:
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Reinforcement. CoRR abs/2406.07515 (2024) - [i26]Elvis Dohmatob, Yunzhen Feng, Arjun Subramonian, Julia Kempe:
Strong Model Collapse. CoRR abs/2410.04840 (2024) - 2023
- [c20]Elvis Dohmatob, Chuan Guo, Morgane Goibert:
Origins of Low-Dimensional Adversarial Perturbations. AISTATS 2023: 9221-9237 - [c19]Meyer Scetbon, Elvis Dohmatob:
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond. AISTATS 2023: 11583-11607 - [c18]Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier:
Contextual bandits with concave rewards, and an application to fair ranking. ICLR 2023 - [i25]Meyer Scetbon, Elvis Dohmatob:
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond. CoRR abs/2301.13486 (2023) - [i24]Elvis Dohmatob, Meyer Scetbon:
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms. CoRR abs/2308.00556 (2023) - [i23]Vivien Cabannes, Elvis Dohmatob, Alberto Bietti:
Scaling Laws for Associative Memories. CoRR abs/2310.02984 (2023) - 2022
- [c17]Nicolas Usunier, Virginie Do, Elvis Dohmatob:
Fast online ranking with fairness of exposure. FAccT 2022: 2157-2167 - [c16]Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR 2022 - [c15]Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi:
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. ICML 2022: 8213-8229 - [i22]Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
Scalable Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2201.08417 (2022) - [i21]Elvis Dohmatob, Alberto Bietti:
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes. CoRR abs/2203.11864 (2022) - [i20]Elvis Dohmatob, Chuan Guo, Morgane Goibert:
Origins of Low-dimensional Adversarial Perturbations. CoRR abs/2203.13779 (2022) - [i19]Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi:
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2207.00486 (2022) - [i18]Nicolas Usunier, Virginie Do, Elvis Dohmatob:
Fast online ranking with fairness of exposure. CoRR abs/2209.13019 (2022) - [i17]Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier:
Contextual bandits with concave rewards, and an application to fair ranking. CoRR abs/2210.09957 (2022) - [i16]Morgane Goibert, Thomas Ricatte, Elvis Dohmatob:
An Adversarial Robustness Perspective on the Topology of Neural Networks. CoRR abs/2211.02675 (2022) - 2021
- [j2]Elvis Dohmatob, Hugo Richard, Ana Luísa Pinho, Bertrand Thirion:
Brain topography beyond parcellations: Local gradients of functional maps. NeuroImage 229: 117706 (2021) - [c14]Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. ICLR 2021 - [i15]Elvis Dohmatob:
Fundamental tradeoffs between memorization and robustness in random features and neural tangent regimes. CoRR abs/2106.02630 (2021) - 2020
- [c13]Louis Faury, Ugo Tanielian, Elvis Dohmatob, Elena Smirnova, Flavian Vasile:
Distributionally Robust Counterfactual Risk Minimization. AAAI 2020: 3850-3857 - [c12]Ugo Tanielian, Thibaut Issenhuth, Elvis Dohmatob, Jérémie Mary:
Learning disconnected manifolds: a no GAN's land. ICML 2020: 9418-9427 - [c11]Elena Smirnova, Elvis Dohmatob:
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes. NeurIPS 2020 - [i14]Ugo Tanielian, Thibaut Issenhuth, Elvis Dohmatob, Jérémie Mary:
Learning disconnected manifolds: a no GANs land. CoRR abs/2006.04596 (2020) - [i13]Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. CoRR abs/2006.09862 (2020) - [i12]Elvis Dohmatob:
Universal Lower-Bounds on Classification Error under Adversarial Attacks and Random Corruption. CoRR abs/2006.09989 (2020) - [i11]Elvis Dohmatob:
Implicit bias of any algorithm: bounding bias via margin. CoRR abs/2011.06550 (2020)
2010 – 2019
- 2019
- [c10]Elvis Dohmatob:
Generalized No Free Lunch Theorem for Adversarial Robustness. ICML 2019: 1646-1654 - [c9]Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene:
Learning Nonsymmetric Determinantal Point Processes. NeurIPS 2019: 6715-6725 - [i10]Elena Smirnova, Elvis Dohmatob, Jérémie Mary:
Distributionally Robust Reinforcement Learning. CoRR abs/1902.08708 (2019) - [i9]Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene:
Learning Nonsymmetric Determinantal Point Processes. CoRR abs/1905.12962 (2019) - [i8]Louis Faury, Ugo Tanielian, Flavian Vasile, Elena Smirnova, Elvis Dohmatob:
Distributionally Robust Counterfactual Risk Minimization. CoRR abs/1906.06211 (2019) - [i7]Morgane Goibert, Elvis Dohmatob:
Adversarial Robustness via Adversarial Label-Smoothing. CoRR abs/1906.11567 (2019) - [i6]Elena Smirnova, Elvis Dohmatob:
On the Convergence of Approximate and Regularized Policy Iteration Schemes. CoRR abs/1909.09621 (2019) - 2018
- [j1]Fouad Hadj-Selem, Tommy Löfstedt, Elvis Dohmatob, Vincent Frouin, Mathieu Dubois, Vincent Guillemot, Edouard Duchesnay:
Continuation of Nesterov's Smoothing for Regression With Structured Sparsity in High-Dimensional Neuroimaging. IEEE Trans. Medical Imaging 37(11): 2403-2413 (2018) - [i5]Elvis Dohmatob:
Limitations of adversarial robustness: strong No Free Lunch Theorem. CoRR abs/1810.04065 (2018) - [i4]Mike Gartrell, Elvis Dohmatob:
Deep Determinantal Point Processes. CoRR abs/1811.07245 (2018) - 2017
- [b1]Elvis Dohmatob:
Enhancement of functional brain connectome analysis by the use of deformable models in the estimation of spatial decompositions of the brain images. (Amélioration de connectivité fonctionnelle par utilisation de modèles déformables dans l'estimation de décompositions spatiales des images de cerveau). University of Paris-Saclay, France, 2017 - 2016
- [c8]Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, Gaël Varoquaux:
Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems. ICASSP 2016: 4752-4756 - [c7]Hubert Pelle, Philippe Ciuciu, Mehdi Rahim, Elvis Dohmatob, Patrice Abry, Virginie van Wassenhove:
Multivariate hurst exponent estimation in FMRI. Application to brain decoding of perceptual learning. ISBI 2016: 996-1000 - [c6]Elvis Dohmatob, Arthur Mensch, Gaël Varoquaux, Bertrand Thirion:
Learning brain regions via large-scale online structured sparse dictionary learning. NIPS 2016: 4610-4618 - 2015
- [c5]Mehdi Rahim, Bertrand Thirion, Alexandre Abraham, Michael Eickenberg, Elvis Dohmatob, Claude Comtat, Gaël Varoquaux:
Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease. MICCAI (1) 2015: 207-214 - [c4]Michael Eickenberg, Elvis Dohmatob, Bertrand Thirion, Gaël Varoquaux:
Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties. MICCAI (1) 2015: 685-693 - [c3]Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, Gaël Varoquaux:
Speeding-Up Model-Selection in Graphnet via Early-Stopping and Univariate Feature-Screening. PRNI 2015: 17-20 - [i3]Elvis Dohmatob:
A simple and efficient algorithm for computing approximate Nash equilibria in two-person zero-sum sequential games with imcomplete information. CoRR abs/1507.07901 (2015) - [i2]Gaël Varoquaux, Michael Eickenberg, Elvis Dohmatob, Bertrand Thirion:
FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging. CoRR abs/1512.06999 (2015) - 2014
- [c2]Elvis Dopgima Dohmatob, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux:
Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging. PRNI 2014: 1-4 - [i1]Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, Gaël Varoquaux:
Region segmentation for sparse decompositions: better brain parcellations from rest fMRI. CoRR abs/1412.3925 (2014) - 2013
- [c1]Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, Gaël Varoquaux:
Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning. MICCAI (2) 2013: 607-615
Coauthor Index
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last updated on 2024-11-14 00:50 CET by the dblp team
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