Adam Wierman
50 papers · 2013–2025 · 9 conferences · across top CS/AI conferences
Achievements
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Century Club
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Conferences
NIPS (20)
ICML (12)
COLT (6)
AISTATS (4)
L4DC (4)
AAAI (1)
ICLR (1)
NSDI (1)
UAI (1)
Top co-authors
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