Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
Convergence Theorems for Entropy-Regularized and Distributional Reinforcement Learning
Yash Jhaveri, Harley Wiltzer, Patrick Shafto +2
In the pursuit of finding an optimal policy, reinforcement learning (RL) methods generally ignore the properties of learned policies apart from their expected return. Thus, even wh…
cs.LG2024
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
Harley Wiltzer, Marc G. Bellemare, David Meger +2
When decisions are made at high frequency, traditional reinforcement learning (RL) methods struggle to accurately estimate action values. In turn, their performance is inconsistent…
cs.LG2024
Structured Evaluation of Synthetic Tabular Data
Scott Cheng-Hsin Yang, Baxter Eaves, Michael Schmidt +2
Tabular data is common yet typically incomplete, small in volume, and access-restricted due to privacy concerns. Synthetic data generation offers potential solutions. Many metrics…