2 papers
cs.LG2026
Meta-reinforcement learning with minimum attention
Shashank Gupta, Pilhwa Lee
Minimum attention applies the least action principle to changes of control concerning state and time, first proposed by Brockett. The involved regularization is highly relevant in…
cs.LG2025
Safe, Efficient, and Robust Reinforcement Learning for Ranking and Diffusion Models
Shashank Gupta
This dissertation investigates how reinforcement learning (RL) methods can be designed to be safe, sample-efficient, and robust. Framed through the unifying perspective of contextu…