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Deep Neural Network Self-Distillation Exploiting Data Representation Invariance 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 1, 页码: 257-269
作者:  Xu, Ting-Bing;  Liu, Cheng-Lin
收藏  |  浏览/下载：177/0  |  提交时间：2022/02/16
Training  Nonlinear distortion  Data models  Neural networks  Knowledge engineering  Network architecture  Generalization error  network compression  representation invariance  self-distillation (SD)  
Time-/Event-Triggered Adaptive Neural Asymptotic Tracking Control of Nonlinear Interconnected Systems With Unmodeled Dynamics and Prescribed Performance 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 11
作者:  Cheng, Ting-Ting;  Niu, Ben;  Zhang, Jia-Ming;  Wang, Ding;  Wang, Zhen-Hua
收藏  |  浏览/下载：252/0  |  提交时间：2022/01/27
Interconnected systems  Artificial neural networks  Closed loop systems  Multi-agent systems  Asymptotic stability  Switches  Stability criteria  Asymptotic tracking control  event-triggered control  neural networks (NNs)  nonlinear interconnected systems  prescribed performance control (PPC)  unmodeled dynamics  
Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 无, 期号: 无, 页码: 无
作者:  Chen, Zhiqiang;  Xu, Ting-Bing;  Du, Changde;  Liu, Cheng-Lin;  He, Huiguang
Adobe PDF(4352Kb)  |  收藏  |  浏览/下载：265/62  |  提交时间：2021/01/27
Conditional accuracy change (CAC), direct criterion, dynamical channel pruning, neural network compression, structure shaping.