Identifying Chemicals Through Dimensionality Reduction. - Emile Anand; Charles Steinhardt; Martin Hansen (CoRR, 2022)

Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations. - Yiheng Lin 001; James A. Preiss; Emile Anand; Yingying Li; Yisong Yue; Adam Wierman (NeurIPS, 2023)

Pseudorandomness of the Sticky Random Walk. - Emile Anand; Chris Umans (CoRR, 2023)

Online Policy Optimization in Unknown Nonlinear Systems. - Yiheng Lin 001; James A. Preiss; Fengze Xie; Emile Anand; Soon-Jo Chung; Yisong Yue; Adam Wierman (COLT, 2024)

The Bit Complexity of Dynamic Algebraic Formulas and Their Determinants. - Emile Anand; Jan van den Brand; Mehrdad Ghadiri; Daniel J. Zhang (ICALP, 2024)

Efficient Reinforcement Learning for Global Decision Making in the Presence of Local Agents at Scale. - Emile Anand; Guannan Qu (CoRR, 2024)

Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning. - Emile Anand; Ishani Karmarkar; Guannan Qu (CoRR, 2024)

Peer-to-Peer Learning Dynamics of Wide Neural Networks. - Shreyas Chaudhari; Srinivasa Pranav; Emile Anand; José M. F. Moura (ICASSP, 2025)

Towards the Pseudorandomness of Expander Random Walks for Read-Once ACC0 circuits. - Emile Anand (CoRR, 2025)

The Structural Complexity of Matrix-Vector Multiplication. - Emile Anand; Jan van den Brand; Rose McCarty (CoRR, 2025)

Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown. - Emile Anand; Sarah Liaw (CoRR, 2025)