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EDP: An Efficient Decomposition and Pruning Scheme for Convolutional Neural Network Compression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 10, 页码: 4499-4513
作者:  Ruan, Xiaofeng;  Liu, Yufan;  Yuan, Chunfeng;  Li, Bing;  Hu, Weiming;  Li, Yangxi;  Maybank, Stephen
Adobe PDF(3625Kb)  |  收藏  |  浏览/下载：343/45  |  提交时间：2021/06/17
Data-driven  low-rank decomposition  model compression and acceleration  structured pruning  
Composite Learning Enhanced Robot Impedance Control 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 3, 页码: 1052-1059
作者:  Sun, Tairen;  Peng, Liang;  Cheng, Long;  Hou, Zeng-Guang;  Pan, Yongping
收藏  |  浏览/下载：274/0  |  提交时间：2020/06/02
Impedance  Convergence  Robots  Stability criteria  Uncertainty  Parameter estimation  Adaptive control  composite adaptation  impedance control  learning control  parameter convergence  robot  
Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 2, 页码: 449-463
作者:  Ma, Zhanyu;  Lai, Yuping;  Kleijn, W. Bastiaan;  Song, Yi-Zhe;  Wang, Liang;  Guo, Jun
收藏  |  浏览/下载：360/0  |  提交时间：2019/07/12
Bayesian estimation  computer vision  Dirichlet process (DP) mixture  inverted Dirichlet distribution  variational learning