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Semisupervised Progressive Representation Learning for Deep Multiview Clustering 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 15
作者:  Chen, Rui;  Tang, Yongqiang;  Xie, Yuan;  Feng, Wenlong;  Zhang, Wensheng
收藏  |  浏览/下载：118/0  |  提交时间：2023/11/17
Representation learning  Training  Data models  Task analysis  Complexity theory  Semisupervised learning  Optimization  Deep clustering  multiview clustering  progressive sample learning  semisupervised learning  
A Self-Attention-Based Deep Reinforcement Learning Approach for AGV Dispatching Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 12
作者:  Wei, Qinglai;  Yan, Yutian;  Zhang, Jie;  Xiao, Jun;  Wang, Cong
收藏  |  浏览/下载：230/0  |  提交时间：2023/01/09
Automated guided vehicle (AGV) dispatching  deep learning  reinforcement learning (RL)  self-attention  
VGN: Value Decomposition With Graph Attention Networks for Multiagent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 14
作者:  Wei, Qinglai;  Li, Yugu;  Zhang, Jie;  Wang, Fei-Yue
收藏  |  浏览/下载：232/0  |  提交时间：2022/07/25
Mathematical models  Task analysis  Games  Q-learning  Neural networks  Behavioral sciences  Training  Deep learning  graph attention networks (GATs)  multiagent systems  reinforcement learning  
Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 3, 页码: 1228-1241
作者:  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2838Kb)  |  收藏  |  浏览/下载：223/3  |  提交时间：2022/06/10
Games  Nash equilibrium  Mathematical model  Markov processes  Convergence  Dynamic programming  Training  Deep reinforcement learning (DRL)  generalized policy iteration (GPI)  Markov game (MG)  Nash equilibrium  Q network  zero sum  
Towards Better Generalization of Deep Neural Networks via Non-Typicality Sampling Scheme 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 11
作者:  Peng, Xinyu;  Wang, Fei-Yue;  Li, Li
收藏  |  浏览/下载：185/0  |  提交时间：2022/06/06
Training  Estimation  Deep learning  Standards  Optimization  Noise measurement  Convergence  Deep learning  generalization performance  nontypicality sampling scheme  stochastic gradient descent (SGD)  
Drill the Cork of Information Bottleneck by Inputting the Most Important Data 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Peng, Xinyu;  Zhang, Jiawei;  Wang, Fei-Yue;  Li, Li
收藏  |  浏览/下载：209/0  |  提交时间：2022/01/27
Training  Signal to noise ratio  Mutual information  Optimization  Convergence  Deep learning  Tools  Information bottleneck (IB) theory  machine learning  minibatch stochastic gradient descent (SGD)  typicality sampling