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cs.LG2026
Pessimistic Minimax Learning for Public-Private Information Games under Unilateral Coverage
Shuze Daniel Liu, Claire Chen, Jiuqi Wang +1
We study offline learning in two-player zero-sum contextual games with public and private information, motivated by strategic settings such as auctions and negotiations with privat…
cs.LG2026
Predicting Plasticity in Deep Continual Learning: A Theoretical Perspective
Jiuqi Wang, Jayanth Srinivasa, Claire Chen +3
Deep continual learning requires models to adapt to new tasks without retraining from scratch. However, neural networks can lose their ability to adapt to new tasks after training…
cs.LG2026
Almost Sure Convergence of Differential Temporal Difference Learning for Average Reward Markov Decision Processes
Ethan Blaser, Jiuqi Wang, Shangtong Zhang
The average reward is a fundamental performance metric in reinforcement learning (RL) focusing on the long-run performance of an agent. Differential temporal difference (TD) learni…