Noah Golowich

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 80

Top Topics

Differential Privacy

Reinforcement Learning

Partially Observable

Top Venues

Publications

Noah Golowich, Ankur Moitra
Edit Distance Robust Watermarks for Language Models. IACR Cryptol. ePrint Arch. 2024 (2024)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. CoRR (2024)
Noah Golowich, Ankur Moitra
Edit Distance Robust Watermarks for Language Models. CoRR (2024)
Noah Golowich, Ankur Moitra
The Role of Inherent Bellman Error in Offline Reinforcement Learning with Linear Function Approximation. CoRR (2024)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. STOC (2024)
Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun
Online Control in Population Dynamics. CoRR (2024)
Noah Golowich, Ankur Moitra
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions. COLT (2024)
Constantinos Daskalakis, Gabriele Farina, Noah Golowich, Tuomas Sandholm, Brian Hu Zhang
A Lower Bound on Swap Regret in Extensive-Form Games. CoRR (2024)
Noah Golowich, Ankur Moitra
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions. CoRR (2024)
Fan Chen, Constantinos Daskalakis, Noah Golowich, Alexander Rakhlin
Near-Optimal Learning and Planning in Separated Latent MDPs. CoRR (2024)
Constantinos Daskalakis, Noah Golowich
Is Efficient PAC Learning Possible with an Oracle That Responds 'Yes' or 'No'? CoRR (2024)
Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
From External to Swap Regret 2.0: An Efficient Reduction for Large Action Spaces. STOC (2024)
Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty
Smooth Nash Equilibria: Algorithms and Complexity. ITCS (2024)
Constantinos Daskalakis, Noah Golowich
Is Efficient PAC Learning Possible with an Oracle That Responds "Yes" or "No"? COLT (2024)
Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich, Robert Kleinberg, Princewill Okoroafor
Improved bounds for calibration via stronger sign preservation games. CoRR (2024)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
On Learning Parities with Dependent Noise. CoRR (2024)
Fan Chen, Constantinos Daskalakis, Noah Golowich, Alexander Rakhlin
Near-Optimal Learning and Planning in Separated Latent MDPs. COLT (2024)
Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
From External to Swap Regret 2.0: An Efficient Reduction and Oblivious Adversary for Large Action Spaces. CoRR (2023)
Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty
Smooth Nash Equilibria: Algorithms and Complexity. CoRR (2023)
Dylan J. Foster, Noah Golowich, Sham M. Kakade
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games. ICML (2023)
Dylan J. Foster, Noah Golowich, Yanjun Han
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient. COLT (2023)
Dylan J. Foster, Noah Golowich, Sham M. Kakade
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games. CoRR (2023)
Dylan J. Foster, Dean P. Foster, Noah Golowich, Alexander Rakhlin
On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. CoRR (2023)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Planning and Learning in Partially Observable Systems via Filter Stability. STOC (2023)
Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang
The Complexity of Markov Equilibrium in Stochastic Games. COLT (2023)
Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis, Emmanouil Zampetakis
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. COLT (2023)
Dylan J. Foster, Noah Golowich, Yanjun Han
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient. CoRR (2023)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. CoRR (2023)
Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. NeurIPS (2023)
Dean Foster, Dylan J. Foster, Noah Golowich, Alexander Rakhlin
On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. COLT (2023)
Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari
A Note on Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. CoRR (2022)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Learning in Observable POMDPs, without Computationally Intractable Oracles. CoRR (2022)
Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis, Manolis Zampetakis
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. CoRR (2022)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Learning in Observable POMDPs, without Computationally Intractable Oracles. NeurIPS (2022)
Adam Block, Yuval Dagan, Noah Golowich, Alexander Rakhlin
Smoothed Online Learning is as Easy as Statistical Learning. COLT (2022)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Planning in Observable POMDPs in Quasipolynomial Time. CoRR (2022)
Constantinos Daskalakis, Noah Golowich
Fast rates for nonparametric online learning: from realizability to learning in games. STOC (2022)
Adam Block, Yuval Dagan, Noah Golowich, Alexander Rakhlin
Smoothed Online Learning is as Easy as Statistical Learning. CoRR (2022)
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina, Maxwell Fishelson, Noah Golowich, Tuomas Sandholm
Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games. STOC (2022)
Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang
The Complexity of Markov Equilibrium in Stochastic Games. CoRR (2022)
Noah Golowich, Ankur Moitra
Can Q-learning be Improved with Advice? COLT (2022)
Noah Golowich, Roi Livni
Littlestone Classes are Privately Online Learnable. CoRR (2021)
Noah Golowich
Differentially Private Nonparametric Regression Under a Growth Condition. CoRR (2021)
Noah Golowich, Roi Livni
Littlestone Classes are Privately Online Learnable. NeurIPS (2021)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
Near-tight closure b ounds for the Littlestone and threshold dimensions. ALT (2021)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
On Deep Learning with Label Differential Privacy. CoRR (2021)
Noah Golowich
Differentially Private Nonparametric Regression Under a Growth Condition. COLT (2021)
Constantinos Daskalakis, Noah Golowich
Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games. CoRR (2021)
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina, Maxwell Fishelson, Noah Golowich, Tuomas Sandholm
Near-Optimal No-Regret Learning for Correlated Equilibria in Multi-Player General-Sum Games. CoRR (2021)
Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
Near-Optimal No-Regret Learning in General Games. CoRR (2021)
Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
Near-Optimal No-Regret Learning in General Games. NeurIPS (2021)
Noah Golowich, Ankur Moitra
Can Q-Learning be Improved with Advice? CoRR (2021)
Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker
On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy. EUROCRYPT (3) (2021)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
Sample-efficient proper PAC learning with approximate differential privacy. STOC (2021)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
Deep Learning with Label Differential Privacy. NeurIPS (2021)
Constantinos Daskalakis, Dylan J. Foster, Noah Golowich
Independent Policy Gradient Methods for Competitive Reinforcement Learning. CoRR (2021)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker
Pure Differentially Private Summation from Anonymous Messages. CoRR (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
Tight last-iterate convergence rates for no-regret learning in multi-player games. CoRR (2020)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
Near-tight closure bounds for Littlestone and threshold dimensions. CoRR (2020)
Constantinos Daskalakis, Dylan J. Foster, Noah Golowich
Independent Policy Gradient Methods for Competitive Reinforcement Learning. NeurIPS (2020)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker
Pure Differentially Private Summation from Anonymous Messages. ITC (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. COLT (2020)
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
Sample-efficient proper PAC learning with approximate differential privacy. CoRR (2020)
Noah Golowich, Madhu Sudan
Round Complexity of Common Randomness Generation: The Amortized Setting. SODA (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
Tight last-iterate convergence rates for no-regret learning in multi-player games. NeurIPS (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. CoRR (2020)
Madhu Sudan, Badih Ghazi, Noah Golowich, Mitali Bafna
Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. SODA (2019)
Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker
Private Heavy Hitters and Range Queries in the Shuffled Model. CoRR (2019)
Noah Golowich, Madhu Sudan
Round Complexity of Common Randomness Generation: The Amortized Setting. CoRR (2019)
Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. ICLR (Poster) (2019)
Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker
On the Power of Multiple Anonymous Messages. IACR Cryptol. ePrint Arch. 2019 (2019)
Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso A. Poggio
Theory of Deep Learning IIb: Optimization Properties of SGD. CoRR (2018)
Noah Golowich, Alexander Rakhlin, Ohad Shamir
Size-Independent Sample Complexity of Neural Networks. COLT (2018)
Noah Golowich
Coloring Chains for Compression with Uncertain Priors. Electron. J. Comb. 25 (4) (2018)
Noah Golowich, Harikrishna Narasimhan, David C. Parkes
Deep Learning for Multi-Facility Location Mechanism Design. IJCAI (2018)
Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. CoRR (2018)
Mitali Bafna, Badih Ghazi, Noah Golowich, Madhu Sudan
Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. Electron. Colloquium Comput. Complex. 25 (2018)
Mitali Bafna, Badih Ghazi, Noah Golowich, Madhu Sudan
Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. CoRR (2018)
Noah Golowich, Alexander Rakhlin, Ohad Shamir
Size-Independent Sample Complexity of Neural Networks. CoRR (2017)
Noah Golowich
The m-degenerate chromatic number of a digraph. Discret. Math. 339 (6) (2016)
Noah Golowich, David Rolnick
Acyclic Subgraphs of Planar Digraphs. Electron. J. Comb. 22 (3) (2015)
Noah Golowich
Resolving a Conjecture on Degree of Regularity of Linear Homogeneous Equations. Electron. J. Comb. 21 (3) (2014)