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Near-Optimal No-Regret Learning in General Games


Aug 16, 2021
Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich

* 40 pages 

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Littlestone Classes are Privately Online Learnable


Jun 25, 2021
Noah Golowich, Roi Livni


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On Deep Learning with Label Differential Privacy


Feb 11, 2021
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

* 26 pages, 4 figures 

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Independent Policy Gradient Methods for Competitive Reinforcement Learning


Jan 11, 2021
Constantinos Daskalakis, Dylan J. Foster, Noah Golowich

* Appeared at NeurIPS 2020 

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Sample-efficient proper PAC learning with approximate differential privacy


Dec 07, 2020
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi

* 40 pages 

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Tight last-iterate convergence rates for no-regret learning in multi-player games


Oct 26, 2020
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis

* To appear at NeurIPS 2020. 41 pages 

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Near-tight closure bounds for Littlestone and threshold dimensions


Jul 07, 2020
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi

* 7 pages 

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Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems


Jan 31, 2020
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman Ozdaglar

* 25 pages 

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Private Heavy Hitters and Range Queries in the Shuffled Model


Aug 29, 2019
Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker

* 30 pages 

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Size-Independent Sample Complexity of Neural Networks


Jun 06, 2018
Noah Golowich, Alexander Rakhlin, Ohad Shamir

* Clarified discussion of scale-sensitive bounds in the existing literature 

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Theory of Deep Learning IIb: Optimization Properties of SGD


Jan 07, 2018
Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso Poggio


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