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cs.LG2024
Robust Offline Reinforcement Learning for Non-Markovian Decision Processes
Ruiquan Huang, Yingbin Liang, Jing Yang
Distributionally robust offline reinforcement learning (RL) aims to find a policy that performs the best under the worst environment within an uncertainty set using an offline data…
cs.LG2024
Non-asymptotic Convergence of Training Transformers for Next-token Prediction
Ruiquan Huang, Yingbin Liang, Jing Yang
Transformers have achieved extraordinary success in modern machine learning due to their excellent ability to handle sequential data, especially in next-token prediction (NTP) task…
cs.LG2024
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups
Fengyu Gao, Ruiquan Huang, Jing Yang
We study the problems of differentially private federated online prediction from experts against both stochastic adversaries and oblivious adversaries. We aim to minimize the avera…