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Adam Wierman

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 15, 2026, 3:09 AM AMS

29

papers

455

total citations

papers (29)

Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward

NEURIPS 2020arXiv

The Power of Predictions in Online Control

NEURIPS 2020arXiv

Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems

NEURIPS 2021arXiv

Multi-Agent Reinforcement Learning in Stochastic Networked Systems

NEURIPS 2021arXiv

Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems

NEURIPS 2021arXiv

Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity

NEURIPS 2022arXiv

Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations

NEURIPS 2023arXiv

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

A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games

NEURIPS 2023arXiv

On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory

NEURIPS 2022arXiv

Online Algorithms with Uncertainty-Quantified Predictions

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions

NEURIPS 2023arXiv

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

Adversarial Attacks on Online Learning to Rank with Click Feedback

NEURIPS 2023arXiv

Robust Learning for Smoothed Online Convex Optimization with Feedback Delay

NEURIPS 2023arXiv

Chasing Convex Functions with Long-term Constraints

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization

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

Online Optimization with Memory and Competitive Control

NEURIPS 2020arXiv

Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees

NEURIPS 2025arXiv

Anytime-Competitive Reinforcement Learning with Policy Prior

NEURIPS 2023arXiv

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

NEURIPS 2025arXiv

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

NEURIPS 2025arXiv

Fusing Reward and Dueling Feedback in Stochastic Bandits

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

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

NEURIPS 2025arXiv

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

Fairness-Regularized Online Optimization with Switching Costs

NEURIPS 2025arXiv

SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems