News

Feb 18, 2026 We introduce GMFS, a scalable framework for multi-agent reinforcement learning that maintains near-optimal performance in heterogeneous populations.
Jun 01, 2025 We demonstrate both theoretically and empirically that Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection can effectively mislead popular algorithms like UCB and Thompson Sampling with minimal attack cost.
Mar 01, 2025 We explore a novel neural population code method to accurately estimate object orientation in Object-Pose Estimation With Neural Population Codes.