Adam Wierman

Improving EV Aggregate Flexibility with End-to-End Learning L4DC 2026 SPADE: Signal-Aware DAG Scheduling and Dynamic Provisioning for Data Processing Clusters OSDI 2026 Approximate Global Convergence of Independent Learning in Multi-Agent Systems AISTATS 2025 Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning ICML 2025 Fusing Reward and Dueling Feedback in Stochastic Bandits ICML 2025 Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data AISTATS 2025 Online Robust Reinforcement Learning Through Monte-Carlo Planning ICML 2025 Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization ICML 2025 Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning ICLR 2025 Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization ICML 2024 Chasing Convex Functions with Long-term Constraints ICML 2024 Combining model-based controller and ML advice via convex reparameterization L4DC 2024 Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation NeurIPS 2024 Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis ICML 2024 Model-Free Robust $φ$-Divergence Reinforcement Learning Using Both Offline and Online Data ICML 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms NeurIPS 2024 Online Algorithms with Uncertainty-Quantified Predictions ICML 2024 Online Budgeted Matching with General Bids NeurIPS 2024 Online Policy Optimization in Unknown Nonlinear Systems COLT 2024 Risk-Sensitive Online Algorithms (Extended Abstract) COLT 2024 Safe Exploitative Play with Untrusted Type Beliefs NeurIPS 2024 Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty ICML 2024 Adversarial Attacks on Online Learning to Rank with Click Feedback NeurIPS 2023 A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games NeurIPS 2023 Anytime-Competitive Reinforcement Learning with Policy Prior NeurIPS 2023 Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions NeurIPS 2023 Contextual Combinatorial Bandits with Probabilistically Triggered Arms ICML 2023 Convergence rates for localized actor-critic in networked Markov potential games UAI 2023 Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations NeurIPS 2023 Online switching control with stability and regret guarantees L4DC 2023 Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems AISTATS 2023 Robust Learning for Smoothed Online Convex Optimization with Feedback Delay NeurIPS 2023 SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems NeurIPS 2023 Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity NeurIPS 2022 Chasing Convex Bodies and Functions with Black-Box Advice COLT 2022 Decentralized Online Convex Optimization in Networked Systems ICML 2022 On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory NeurIPS 2022 Data-driven Competitive Algorithms for Online Knapsack and Set Cover AAAI 2021 Multi-Agent Reinforcement Learning in Stochastic Networked Systems NeurIPS 2021 Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems NeurIPS 2021 Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems NeurIPS 2021 Stable Online Control of Linear Time-Varying Systems L4DC 2021 Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-Learning COLT 2020 Online Optimization with Memory and Competitive Control NeurIPS 2020 Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward NeurIPS 2020 Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems L4DC 2020 The Power of Predictions in Online Control NeurIPS 2020 An Online Algorithm for Smoothed Regression and LQR Control AISTATS 2019 Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization NeurIPS 2019 Smoothed Online Convex Optimization in High Dimensions via Online Balanced Descent COLT 2018 GRASS: Trimming Stragglers in Approximation Analytics NSDI 2014 A Tale of Two Metrics: Simultaneous Bounds on Competitiveness and Regret COLT 2013