Baoxiang Wang
30 papers · 2016–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (54) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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Research topics
Reinforcement Learning
(22)
Machine Learning
(20)
Methods
(19)
Optimization & Theory
(15)
Artificial Intelligence
(13)
Core AI
(12)
Learning Types Β· Machine Learning
(11)
Mathematics & Optimization
(8)
Optimization
(8)
Applications
(5)
Deep Learning
(4)
Learning Types Β· Deep Learning
(4)
Application Areas
(3)
Computer Vision
(1)
Data Science & Analytics
(1)
Keywords
reinforcement learning
(8)
multi-agent reinforcement learning
(7)
regret bound
(6)
policy optimization
(4)
nash equilibrium
(3)
multi-agent system
(3)
credit assignment
(3)
value function
(2)
offline reinforcement learning
(2)
convergence rate
(2)
last-iterate convergence
(2)
continuous control
(2)
markov decision process
(2)
bandit feedback
(2)
markov game
(2)
differential privacy
(2)
high-dimensional modeling
(1)
online learning
(1)
image generation
(1)
sequence modeling
(1)
Papers
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
Last-iterate Convergence in Regularized Graphon Mean Field Game
AAAI 2025
Learning Imperfect Information Extensive-form Games with Last-iterate Convergence under Bandit Feedback
ICML 2025
Learning to Communicate Through Implicit Communication Channels
ICLR 2025
Learning to Negotiate via Voluntary Commitment
AISTATS 2025
Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions
AAAI 2025
Multi-Agent Credit Assignment with Pretrained Language Models
AISTATS 2025
Reward Translation via Reward Machine in Semi-Alignable MDPs
ICML 2025
Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
ICLR 2025
Carbon Market Simulation with Adaptive Mechanism Design
IJCAI 2024
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games
AISTATS 2024
Few-Shot Diffusion Models Escape the Curse of Dimensionality
NeurIPS 2024
Online Control with Adversarial Disturbance for Continuous-time Linear Systems
NeurIPS 2024
Online Policy Optimization for Robust Markov Decision Process
UAI 2024
On Stationary Point Convergence of PPO-Clip
ICLR 2024
Relative Policy-Transition Optimization for Fast Policy Transfer
AAAI 2024
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning
IJCAI 2023
Information Design in Multi-Agent Reinforcement Learning
NeurIPS 2023
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
ICLR 2023
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback
NeurIPS 2023
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning
AAAI 2023
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
NeurIPS 2023
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning
ICML 2022
The Gambler's Problem and Beyond
ICLR 2020
Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control
IJCAI 2019
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces
NeurIPS 2019
Recurrent Existence Determination Through Policy Optimization
IJCAI 2019
Policy Optimization with Second-Order Advantage Information
IJCAI 2018
Contextual Combinatorial Cascading Bandits
ICML 2016