4 citations · 4 across the 6 of their papers we have counts for
5 papers · 1 filter
SRG: Score-based Relaxation-guided Generation for Mixed Integer Linear Programming
Ruobing Wang, Xin Li, Yujie Fang +1
We propose Score-based Relaxation-guided Generation (SRG), a generative framework based on an approximate formulation of relaxation-guided stochastic differential equations (SDEs)…
Offline Meta-Reinforcement Learning with Flow-Based Task Inference and Adaptive Correction of Feature Overgeneralization
Min Wang, Xin Li, Mingzhong Wang +1
Offline meta-reinforcement learning (OMRL) combines the strengths of learning from diverse datasets in offline RL with the adaptability to new tasks of meta-RL, promising safe and…
Wavelet Predictive Representations for Non-Stationary Reinforcement Learning
Min Wang, Xin Li, Ye He +4
The real world is inherently non-stationary, with ever-changing factors, such as weather conditions and traffic flows, making it challenging for agents to adapt to varying environm…
Towards Control-Centric Representations in Reinforcement Learning from Images
Chen Liu, Hongyu Zang, Xin Li +5
Image-based Reinforcement Learning is a practical yet challenging task. A major hurdle lies in extracting control-centric representations while disregarding irrelevant information.…
Good Better Best: Self-Motivated Imitation Learning for noisy Demonstrations
Ye Yuan, Xin Li, Yong Heng +2
Imitation Learning (IL) aims to discover a policy by minimizing the discrepancy between the agent's behavior and expert demonstrations. However, IL is susceptible to limitations im…