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Noah Golowich
Noah Golowich
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Size-independent sample complexity of neural networks
N Golowich, A Rakhlin, O Shamir
Conference On Learning Theory, 297-299, 2018
5602018
A convergence analysis of gradient descent for deep linear neural networks
S Arora, N Cohen, N Golowich, W Hu
arXiv preprint arXiv:1810.02281, 2018
2532018
Independent policy gradient methods for competitive reinforcement learning
C Daskalakis, DJ Foster, N Golowich
Advances in neural information processing systems 33, 5527-5540, 2020
1662020
Deep learning with label differential privacy
B Ghazi, N Golowich, R Kumar, P Manurangsi, C Zhang
Advances in neural information processing systems 34, 27131-27145, 2021
1282021
Last iterate is slower than averaged iterate in smooth convex-concave saddle point problems
N Golowich, S Pattathil, C Daskalakis, A Ozdaglar
Conference on Learning Theory, 1758-1784, 2020
1072020
On the power of multiple anonymous messages: Frequency estimation and selection in the shuffle model of differential privacy
B Ghazi, N Golowich, R Kumar, R Pagh, A Velingker
Annual International Conference on the Theory and Applications of …, 2021
862021
Near-optimal no-regret learning in general games
C Daskalakis, M Fishelson, N Golowich
Advances in Neural Information Processing Systems 34, 27604-27616, 2021
812021
Tight last-iterate convergence rates for no-regret learning in multi-player games
N Golowich, S Pattathil, C Daskalakis
34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
812020
Deep Learning for Multi-Facility Location Mechanism Design.
N Golowich, H Narasimhan, DC Parkes
IJCAI, 261-267, 2018
812018
The complexity of markov equilibrium in stochastic games
C Daskalakis, N Golowich, K Zhang
The Thirty Sixth Annual Conference on Learning Theory, 4180-4234, 2023
592023
Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games
I Anagnostides, C Daskalakis, G Farina, M Fishelson, N Golowich, ...
Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022
542022
Pure differentially private summation from anonymous messages
B Ghazi, N Golowich, R Kumar, P Manurangsi, R Pagh, A Velingker
arXiv preprint arXiv:2002.01919, 2020
512020
Smoothed online learning is as easy as statistical learning
A Block, Y Dagan, N Golowich, A Rakhlin
Conference on Learning Theory, 1716-1786, 2022
342022
Planning and learning in partially observable systems via filter stability
N Golowich, A Moitra, D Rohatgi
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 349-362, 2023
32*2023
Learning in observable pomdps, without computationally intractable oracles
N Golowich, A Moitra, D Rohatgi
Advances in neural information processing systems 35, 1458-1473, 2022
272022
Tight guarantees for interactive decision making with the decision-estimation coefficient
DJ Foster, N Golowich, Y Han
The Thirty Sixth Annual Conference on Learning Theory, 3969-4043, 2023
252023
Sample-efficient proper PAC learning with approximate differential privacy
B Ghazi, N Golowich, R Kumar, P Manurangsi
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021
252021
Fast rates for nonparametric online learning: from realizability to learning in games
C Daskalakis, N Golowich
Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022
182022
Model-free reinforcement learning with the decision-estimation coefficient
DJ Foster, N Golowich, J Qian, A Rakhlin, A Sekhari
Advances in Neural Information Processing Systems 36, 2024
16*2024
On the complexity of multi-agent decision making: From learning in games to partial monitoring
D Foster, DJ Foster, N Golowich, A Rakhlin
The Thirty Sixth Annual Conference on Learning Theory, 2678-2792, 2023
102023
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