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Baoxiang Wang

30 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (9) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (7) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (90) πŸ’Ž Century Club (30) ⚑ Prolific Year (6)

Conferences

ICLR (6) NIPS (6) ICML (5) IJCAI (5) AAAI (4) AISTATS (3) UAI (1)

Top co-authors

Shuai Li (9) Jing Dong (6) Canzhe Zhao (5) Hongyuan Zha (4) Wenhao Li (4) Ruofeng Yang (3) ruinan Jin (3) Kun Kuang (3) Yaoliang Yu (3) Shengyu Zhang (2)

Research topics

Differential Privacy (1)

Keywords

multi-agent reinforcement learning (6) reinforcement learning (6) regret bound (4) policy optimization (4) differential privacy (2) markov game (2) credit assignment (2) continuous control (2) multi-agent system (2) nash equilibrium (2) adversarial learning (1) high-dimensional modeling (1) game theory (1) function approximation (1) regret analysis (1) online learning (1) markov decision process (1) image generation (1) dynamics modeling (1) domain randomization (1)

Papers

Learning Imperfect Information Extensive-form Games with Last-iterate Convergence under Bandit Feedback ICML 2025
Learning to Negotiate via Voluntary Commitment AISTATS 2025
Multi-Agent Credit Assignment with Pretrained Language Models AISTATS 2025
Learning to Communicate Through Implicit Communication Channels ICLR 2025
Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling ICLR 2025
A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD ICML 2025
Improved Approximation Algorithms for $k$-Submodular Maximization via Multilinear Extension ICLR 2025
Reward Translation via Reward Machine in Semi-Alignable MDPs ICML 2025
Last-iterate Convergence in Regularized Graphon Mean Field Game AAAI 2025
Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions AAAI 2025
Online Policy Optimization for Robust Markov Decision Process UAI 2024
Online Control with Adversarial Disturbance for Continuous-time Linear Systems NIPS 2024
Few-Shot Diffusion Models Escape the Curse of Dimensionality NIPS 2024
Relative Policy-Transition Optimization for Fast Policy Transfer AAAI 2024
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games AISTATS 2024
On Stationary Point Convergence of PPO-Clip ICLR 2024
Carbon Market Simulation with Adaptive Mechanism Design IJCAI 2024
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition ICLR 2023
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning AAAI 2023
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback NIPS 2023
Information Design in Multi-Agent Reinforcement Learning NIPS 2023
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning NIPS 2023
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning IJCAI 2023
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning ICML 2022
The Gambler's Problem and Beyond ICLR 2020
Recurrent Existence Determination Through Policy Optimization IJCAI 2019
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NIPS 2019
Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control IJCAI 2019
Policy Optimization with Second-Order Advantage Information IJCAI 2018
Contextual Combinatorial Cascading Bandits ICML 2016