Search Results for author: Cheng Zhou

Found 9 papers, 1 papers with code

Relative Policy-Transition Optimization for Fast Policy Transfer

no code implementations13 Jun 2022 Jiawei Xu, Cheng Zhou, Yizheng Zhang, Baoxiang Wang, Lei Han

Integrating the two algorithms results in the complete Relative Policy-Transition Optimization (RPTO) algorithm, in which the policy interacts with the two environments simultaneously, such that data collections from two environments, policy and transition updates are completed in one closed loop to form a principled learning framework for policy transfer.

Continuous Control LEMMA +1

A General Theory of Relativity in Reinforcement Learning

no code implementations29 Sep 2021 Lei Han, Cheng Zhou, Yizheng Zhang

We propose a new general theory measuring the relativity between two arbitrary Markov Decision Processes (MDPs) from the perspective of reinforcement learning (RL).

reinforcement-learning Reinforcement Learning (RL)

Hierarchical Disentangled Representation Learning for Outdoor Illumination Estimation and Editing

no code implementations ICCV 2021 Piaopiao Yu, Jie Guo, Fan Huang, Cheng Zhou, Hongwei Che, Xiao Ling, Yanwen Guo

However, naively compressing an outdoor panorama into a low-dimensional latent vector, as existing models have done, causes two major problems.

Representation Learning

An Action Recognition network for specific target based on rMC and RPN

no code implementations19 Jun 2019 Mingjie Li, Youqian Feng, Zhonghai Yin, Cheng Zhou, Fanghao Dong, Yu-an Lin, Yuhao Dong

Meanwhile, the action recognition network is tested in our gesture and body posture data sets for specific target.

Action Recognition regression

Impoved RPN for Single Targets Detection based on the Anchor Mask Net

no code implementations18 Jun 2019 Mingjie Li, Youqian Feng, Zhonghai Yin, Cheng Zhou, Fanghao Dong

Common target detection is usually based on single frame images, which is vulnerable to affected by the similar targets in the image and not applicable to video images.

DHER: Hindsight Experience Replay for Dynamic Goals

1 code implementation ICLR 2019 Meng Fang, Cheng Zhou, Bei Shi, Boqing Gong, Jia Xu, Tong Zhang

Dealing with sparse rewards is one of the most important challenges in reinforcement learning (RL), especially when a goal is dynamic (e. g., to grasp a moving object).

Object Tracking Reinforcement Learning (RL)

An Extreme-Value Approach for Testing the Equality of Large U-Statistic Based Correlation Matrices

no code implementations11 Feb 2015 Cheng Zhou, Fang Han, Xinsheng Zhang, Han Liu

Theoretically, we develop a theory for testing the equality of U-statistic based correlation matrices.

valid

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