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ORCIDSamy Jelassi
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2020 – today
- 2024
[c11]Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener:
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. ICML 2024- [c10]Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach:
Repeat After Me: Transformers are Better than State Space Models at Copying. ICML 2024 - [i19]Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach:
Repeat After Me: Transformers are Better than State Space Models at Copying. CoRR abs/2402.01032 (2024) - [i18]Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener:
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. CoRR abs/2402.14688 (2024) - [i17]Ahmet Cagri Duzgun, Samy Jelassi, Yuanzhi Li:
How Does Overparameterization Affect Features? CoRR abs/2407.00968 (2024) - [i16]Kaiying Hou, David Brandfonbrener, Sham M. Kakade, Samy Jelassi, Eran Malach:
Universal Length Generalization with Turing Programs. CoRR abs/2407.03310 (2024) - 2023
- [b1]Samy Jelassi:
Algorithmic and architectural implicit biases in deep learning. Princeton University, USA, 2023 - [i15]Samy Jelassi, Boris Hanin, Ziwei Ji, Sashank J. Reddi, Srinadh Bhojanapalli, Sanjiv Kumar:
Depth Dependence of μP Learning Rates in ReLU MLPs. CoRR abs/2305.07810 (2023) - [i14]Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton:
Length Generalization in Arithmetic Transformers. CoRR abs/2306.15400 (2023) - 2022
- [j2]Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna:
Depth separation beyond radial functions. J. Mach. Learn. Res. 23: 122:1-122:56 (2022) - [j1]Aaron Defazio, Samy Jelassi:
A Momentumized, Adaptive, Dual Averaged Gradient Method. J. Mach. Learn. Res. 23: 144:1-144:34 (2022) - [c9]Samy Jelassi, Yuanzhi Li:
Towards understanding how momentum improves generalization in deep learning. ICML 2022: 9965-10040 - [c8]Samy Jelassi, Michael E. Sander, Yuanzhi Li:
Vision Transformers provably learn spatial structure. NeurIPS 2022 - [i13]Samy Jelassi, Yuanzhi Li:
Towards understanding how momentum improves generalization in deep learning. CoRR abs/2207.05931 (2022) - [i12]Samy Jelassi, David Dobre, Arthur Mensch, Yuanzhi Li, Gauthier Gidel:
Dissecting adaptive methods in GANs. CoRR abs/2210.04319 (2022) - [i11]Samy Jelassi, Michael E. Sander, Yuanzhi Li:
Vision Transformers provably learn spatial structure. CoRR abs/2210.09221 (2022) - 2021
- [c7]Jad Rahme, Samy Jelassi, Joan Bruna, S. Matthew Weinberg:
A Permutation-Equivariant Neural Network Architecture For Auction Design. AAAI 2021: 5664-5672 - [c6]Jad Rahme, Samy Jelassi, S. Matthew Weinberg
:
Auction Learning as a Two-Player Game. ICLR 2021 - [i10]Aaron Defazio, Samy Jelassi:
Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization. CoRR abs/2101.11075 (2021) - [i9]Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna:
Depth separation beyond radial functions. CoRR abs/2102.01621 (2021) - 2020
- [c5]Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna:
Extra-gradient with player sampling for faster convergence in n-player games. ICML 2020: 4736-4745 - [c4]Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna:
A mean-field analysis of two-player zero-sum games. NeurIPS 2020 - [i8]Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna:
A mean-field analysis of two-player zero-sum games. CoRR abs/2002.06277 (2020) - [i7]Jad Rahme, Samy Jelassi, Joan Bruna, S. Matthew Weinberg:
A Permutation-Equivariant Neural Network Architecture For Auction Design. CoRR abs/2003.01497 (2020) - [i6]Jad Rahme, Samy Jelassi, S. Matthew Weinberg:
Auction learning as a two-player game. CoRR abs/2006.05684 (2020) - [i5]Samy Jelassi, Aaron Defazio:
Dual Averaging is Surprisingly Effective for Deep Learning Optimization. CoRR abs/2010.10502 (2020)
2010 – 2019
- 2019
- [c3]Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden:
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically. ICML 2019: 5508-5517 - [c2]Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis R. Bach, Robert M. Gower:
Towards closing the gap between the theory and practice of SVRG. NeurIPS 2019: 646-656 - [i4]Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden:
Global convergence of neuron birth-death dynamics. CoRR abs/1902.01843 (2019) - [i3]Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna:
Extra-gradient with player sampling for provable fast convergence in n-player games. CoRR abs/1905.12363 (2019) - [i2]Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis R. Bach, Robert M. Gower:
Towards closing the gap between the theory and practice of SVRG. CoRR abs/1908.02725 (2019) - 2018
- [c1]Thomas Pumir, Samy Jelassi, Nicolas Boumal:
Smoothed analysis of the low-rank approach for smooth semidefinite programs. NeurIPS 2018: 2287-2296 - [i1]Thomas Pumir, Samy Jelassi, Nicolas Boumal:
Smoothed analysis of the low-rank approach for smooth semidefinite programs. CoRR abs/1806.03763 (2018)
Coauthor Index
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last updated on 2024-09-13 00:38 CEST by the dblp team
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