← Authors

Adam Wierman

50 papers · 2013–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (5) πŸ—ΊοΈ Taxonomy Completionist (19) πŸƒ Academic Marathon (12) 🏠 Conference Loyalist (20) 🀝 Dynamic Duo (13) 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”¬ Deep Specialist (19) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (8) ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (152) πŸ’Ž Century Club (50)

Conferences

NIPS (20) ICML (12) COLT (6) AISTATS (4) L4DC (4) AAAI (1) ICLR (1) NSDI (1) UAI (1)

Top co-authors

Yiheng Lin (13) Guannan Qu (10) Laixi Shi (7) Mohammad Hajiesmaili (7) Nicolas Christianson (6) Eric Mazumdar (6) Bo Sun (5) Yisong Yue (5) Shaolei Ren (5) Tongxin Li (4)

Keywords

competitive ratio (11) online algorithm (6) regret bound (6) online convex optimization (5) reinforcement learning (4) online control (4) learning-augmented algorithm (4) multi-agent reinforcement learning (4) multi-agent system (4) switching cost (4) dynamic regret (4) smoothed online convex optimization (3) multi-armed bandit (3) markov decision process (3) sample complexity (3) online optimization (3) networked system (3) linear time-varying system (3) stochastic game (2) regret analysis (2)

Papers

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