1 citations · 1 across the 3 of their papers we have counts for
4 papers
Improving Online Reinforcement Learning via Bidirectional Behavior Prior Distillation
Gong Gao, Xiao Lai, Jiaji Shen +3
Online reinforcement learning (RL) algorithms frequently exhibit poor sample efficiency and unstable learning dynamics, stemming from systematic critic estimation errors that are e…
Expert Behavior Prior Reinforcement Learning
Gong Gao, Weidong Zhao, Xianhui Liu +1
Behavior prior reinforcement learning (BPRL) has emerged as a promising paradigm to improve sample efficiency in online reinforcement learning (RL) by leveraging policy priors deri…
Improving Policy Exploitation in Online Reinforcement Learning with Instant Retrospect Action
Gong Gao, Weidong Zhao, Xianhui Liu +1
Existing value-based online reinforcement learning (RL) algorithms suffer from slow policy exploitation due to ineffective exploration and delayed policy updates. To address these…
Reconstructing the Image Stitching Pipeline: Integrating Fusion and Rectangling into a Unified Inpainting Model
Ziqi Xie, Weidong Zhao, Xianhui Liu +2
Deep learning-based image stitching pipelines are typically divided into three cascading stages: registration, fusion, and rectangling. Each stage requires its own network training…