PhD student, University of California, Berkeley
2 papers at NeurIPS 2025
A new approach to learning offline safe reinforcement learning with high performance and safety guarantee
Our paper shows that ensemble learning via majority voting achieves exponentially faster risk decay, improving base learners with slow rates.
