Adam Wierman

14

Papers

17

Total Citations

Papers (14)

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning

Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees

Fusing Reward and Dueling Feedback in Stochastic Bandits

Conformal Risk Training: End-to-End Optimization of Conformal Risk Control

Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach

NeurIPS 2025arXiv

Chasing Convex Functions with Long-term Constraints

Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis

Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty

Online Algorithms with Uncertainty-Quantified Predictions

Fairness-Regularized Online Optimization with Switching Costs

NeurIPS 2025arXiv

Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data

Maximizing the Value of Predictions in Control: Accuracy Is Not Enough

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization