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语种:英语
出处:IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
专题:多模态人工智能系统全国重点实验室
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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
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浏览/下载:92/0
  |  
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:211/0
  |  
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:214/0
  |  
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
收藏
  |  
浏览/下载:198/0
  |  
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
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  |  
浏览/下载:164/0
  |  
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)
Weakly Aligned Feature Fusion for Multimodal Object Detection
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:
Zhang, Lu
;
Liu, Zhiyong
;
Zhu, Xiangyu
;
Song, Zhan
;
Yang, Xu
;
Lei, Zhen
;
Qiao, Hong
收藏
  |  
浏览/下载:200/0
  |  
提交时间:2022/01/27
Object detection
Feature extraction
Detectors
Robustness
Cameras
Automation
Training
Deep learning
feature fusion
multimodal object detection
pedestrian detection
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:188/0
  |  
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
Optimal Elevator Group Control via Deep Asynchronous Actor-Critic Learning
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5245-5256
作者:
Wei, Qinglai
;
Wang, Lingxiao
;
Liu, Yu
;
Polycarpou, Marios M.
Adobe PDF(4019Kb)
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收藏
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浏览/下载:328/75
  |  
提交时间:2021/03/08
Elevators
Optimal control
Backpropagation
Machine learning
Neural networks
Learning (artificial intelligence)
Actor
–critic
adaptive dynamic programming
deep learning (DL)
elevator group control (EGC)
optimal control
reinforcement learning (RL)
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 6, 页码: 2064-2076
作者:
Li, Haoran
;
Zhang, Qichao
;
Zhao, Dongbin
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Adobe PDF(4274Kb)
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收藏
  |  
浏览/下载:367/114
  |  
提交时间:2020/08/03
Robot sensing systems
Navigation
Entropy
Neural networks
Task analysis
Planning
Automatic exploration
deep reinforcement learning (DRL)
optimal decision
partial observation