Resolving a Conjecture on Degree of Regularity of Linear Homogeneous Equations. - Noah Golowich (Electron. J. Comb., 2014)

Acyclic Subgraphs of Planar Digraphs. - Noah Golowich; David Rolnick (Electron. J. Comb., 2015)

The m-degenerate chromatic number of a digraph. - Noah Golowich (Discret. Math., 2016)

Size-Independent Sample Complexity of Neural Networks. - Noah Golowich; Alexander Rakhlin; Ohad Shamir (COLT, 2018)

Deep Learning for Multi-Facility Location Mechanism Design. - Noah Golowich; Harikrishna Narasimhan; David C. Parkes (IJCAI, 2018)

Coloring Chains for Compression with Uncertain Priors. - Noah Golowich (Electron. J. Comb., 2018)

Theory of Deep Learning IIb: Optimization Properties of SGD. - Chiyuan Zhang; Qianli Liao; Alexander Rakhlin; Brando Miranda; Noah Golowich; Tomaso A. Poggio (CoRR, 2018)

Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. - Mitali Bafna; Badih Ghazi; Noah Golowich; Madhu Sudan 001 (Electron. Colloquium Comput. Complex., 2018)

A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. - Sanjeev Arora; Nadav Cohen; Noah Golowich; Wei Hu 014 (ICLR (Poster), 2019)

Private Heavy Hitters and Range Queries in the Shuffled Model. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Rasmus Pagh; Ameya Velingker (CoRR, 2019)

On the Power of Multiple Anonymous Messages. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Rasmus Pagh; Ameya Velingker (IACR Cryptol. ePrint Arch., 2019)

Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. - Noah Golowich; Sarath Pattathil; Constantinos Daskalakis; Asuman E. Ozdaglar (COLT, 2020)

Pure Differentially Private Summation from Anonymous Messages. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Pasin Manurangsi; Rasmus Pagh; Ameya Velingker (ITC, 2020)

Independent Policy Gradient Methods for Competitive Reinforcement Learning. - Constantinos Daskalakis; Dylan J. Foster; Noah Golowich (NeurIPS, 2020)

Tight last-iterate convergence rates for no-regret learning in multi-player games. - Noah Golowich; Sarath Pattathil; Constantinos Daskalakis (NeurIPS, 2020)

Round Complexity of Common Randomness Generation: The Amortized Setting. - Noah Golowich; Madhu Sudan 001 (SODA, 2020)

Near-tight closure bounds for Littlestone and threshold dimensions. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Pasin Manurangsi (CoRR, 2020)

Near-tight closure b ounds for the Littlestone and threshold dimensions. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Pasin Manurangsi (ALT, 2021)

Differentially Private Nonparametric Regression Under a Growth Condition. - Noah Golowich (COLT, 2021)

On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Rasmus Pagh; Ameya Velingker (EUROCRYPT (3), 2021)

Near-Optimal No-Regret Learning in General Games. - Constantinos Daskalakis; Maxwell Fishelson; Noah Golowich (NeurIPS, 2021)

Deep Learning with Label Differential Privacy. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Pasin Manurangsi; Chiyuan Zhang (NeurIPS, 2021)

Littlestone Classes are Privately Online Learnable. - Noah Golowich; Roi Livni (NeurIPS, 2021)

Sample-efficient proper PAC learning with approximate differential privacy. - Badih Ghazi; Noah Golowich; Ravi Kumar 001; Pasin Manurangsi (STOC, 2021)

Smoothed Online Learning is as Easy as Statistical Learning. - Adam Block; Yuval Dagan; Noah Golowich; Alexander Rakhlin (COLT, 2022)

Can Q-learning be Improved with Advice? - Noah Golowich; Ankur Moitra (COLT, 2022)

Learning in Observable POMDPs, without Computationally Intractable Oracles. - Noah Golowich; Ankur Moitra; Dhruv Rohatgi (NeurIPS, 2022)

Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games. - Ioannis Anagnostides; Constantinos Daskalakis; Gabriele Farina; Maxwell Fishelson; Noah Golowich; Tuomas Sandholm (STOC, 2022)

Fast rates for nonparametric online learning: from realizability to learning in games. - Constantinos Daskalakis; Noah Golowich (STOC, 2022)

Planning in Observable POMDPs in Quasipolynomial Time. - Noah Golowich; Ankur Moitra; Dhruv Rohatgi (CoRR, 2022)

A Note on Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. - Dylan J. Foster; Noah Golowich; Jian Qian; Alexander Rakhlin; Ayush Sekhari (CoRR, 2022)

STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. - Constantinos Daskalakis; Noah Golowich; Stratis Skoulakis; Emmanouil Zampetakis (COLT, 2023)

The Complexity of Markov Equilibrium in Stochastic Games. - Constantinos Daskalakis; Noah Golowich; Kaiqing Zhang (COLT, 2023)

On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. - Dean P. Foster; Dylan J. Foster; Noah Golowich; Alexander Rakhlin (COLT, 2023)

Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient. - Dylan J. Foster; Noah Golowich; Yanjun Han (COLT, 2023)

Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games. - Dylan J. Foster; Noah Golowich; Sham M. Kakade (ICML, 2023)

Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. - Dylan J. Foster; Noah Golowich; Jian Qian; Alexander Rakhlin; Ayush Sekhari (NeurIPS, 2023)

Planning and Learning in Partially Observable Systems via Filter Stability. - Noah Golowich; Ankur Moitra; Dhruv Rohatgi (STOC, 2023)

From External to Swap Regret 2.0: An Efficient Reduction and Oblivious Adversary for Large Action Spaces. - Yuval Dagan; Constantinos Daskalakis; Maxwell Fishelson; Noah Golowich (CoRR, 2023)

Near-Optimal Learning and Planning in Separated Latent MDPs. - Fan Chen; Constantinos Daskalakis; Noah Golowich; Alexander Rakhlin (COLT, 2024)

Is Efficient PAC Learning Possible with an Oracle That Responds "Yes" or "No"? - Constantinos Daskalakis; Noah Golowich (COLT, 2024)

Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions. - Noah Golowich; Ankur Moitra (COLT, 2024)

Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. - Noah Golowich; Ankur Moitra; Dhruv Rohatgi (FOCS, 2024)

Smooth Nash Equilibria: Algorithms and Complexity. - Constantinos Daskalakis; Noah Golowich; Nika Haghtalab; Abhishek Shetty (ITCS, 2024)

Online Control in Population Dynamics. - Noah Golowich; Elad Hazan; Zhou Lu; Dhruv Rohatgi; Y. Jennifer Sun (NeurIPS, 2024)

Edit Distance Robust Watermarks via Indexing Pseudorandom Codes. - Noah Golowich; Ankur Moitra (NeurIPS, 2024)

The Role of Inherent Bellman Error in Offline Reinforcement Learning with Linear Function Approximation. - Noah Golowich; Ankur Moitra (RLJ, 2024)

From External to Swap Regret 2.0: An Efficient Reduction for Large Action Spaces. - Yuval Dagan; Constantinos Daskalakis; Maxwell Fishelson; Noah Golowich (STOC, 2024)

Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. - Noah Golowich; Ankur Moitra; Dhruv Rohatgi (STOC, 2024)

On Learning Parities with Dependent Noise. - Noah Golowich; Ankur Moitra; Dhruv Rohatgi (CoRR, 2024)

A Lower Bound on Swap Regret in Extensive-Form Games. - Constantinos Daskalakis; Gabriele Farina; Noah Golowich; Tuomas Sandholm; Brian Hu Zhang (CoRR, 2024)

Improved bounds for calibration via stronger sign preservation games. - Yuval Dagan; Constantinos Daskalakis; Maxwell Fishelson; Noah Golowich; Robert Kleinberg; Princewill Okoroafor (CoRR, 2024)

Edit Distance Robust Watermarks for Language Models. - Noah Golowich; Ankur Moitra (IACR Cryptol. ePrint Arch., 2024)

Breaking the T^(2/3) Barrier for Sequential Calibration. - Yuval Dagan; Constantinos Daskalakis; Maxwell Fishelson; Noah Golowich; Robert Kleinberg; Princewill Okoroafor (STOC, 2025)

The Role of Sparsity for Length Generalization in Transformers. - Noah Golowich; Samy Jelassi; David Brandfonbrener; Sham M. Kakade; Eran Malach (CoRR, 2025)

High-Dimensional Calibration from Swap Regret. - Maxwell Fishelson; Noah Golowich; Mehryar Mohri; Jon Schneider (CoRR, 2025)