1 citations · 1 across the 13 of their papers we have counts for
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Learning Through Game: Skewed Transfer of Tabular Knowledge to Strengthen Image Model
Longfei Huang, Shangdong Yang, Yang Yang
Multimodal tabular-image learning is gaining growing attention, yet it faces challenges due to tabular data unavailable at test time. A practical solution involves transferring tab…
Model-Based Offline Reinforcement Learning with Adversarial Data Augmentation
Hongye Cao, Fan Feng, Jing Huo +4
Model-based offline Reinforcement Learning (RL) constructs environment models from offline datasets to perform conservative policy optimization. Existing approaches focus on learni…
Bellman Error Centering
Xingguo Chen, Yu Gong, Shangdong Yang +1
This paper revisits the recently proposed reward centering algorithms including simple reward centering (SRC) and value-based reward centering (VRC), and points out that SRC is ind…
A Variance Minimization Approach to Temporal-Difference Learning
Xingguo Chen, Yu Gong, Shangdong Yang +1
Fast-converging algorithms are a contemporary requirement in reinforcement learning. In the context of linear function approximation, the magnitude of the smallest eigenvalue of th…
Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy Gradient
Wubing Chen, Wenbin Li, Xiao Liu +2
Cooperative multi-agent policy gradient (MAPG) algorithms have recently attracted wide attention and are regarded as a general scheme for the multi-agent system. Credit assignment…
Keeping Minimal Experience to Achieve Efficient Interpretable Policy Distillation
Xiao Liu, Shuyang Liu, Wenbin Li +2
Although deep reinforcement learning has become a universal solution for complex control tasks, its real-world applicability is still limited because lacking security guarantees fo…
Online Attentive Kernel-Based Temporal Difference Learning
Guang Yang, Xingguo Chen, Shangdong Yang +3
With rising uncertainty in the real world, online Reinforcement Learning (RL) has been receiving increasing attention due to its fast learning capability and improving data efficie…