CASIA OpenIR

浏览/检索结果: 共21条,第1-10条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
An Empirical Study on Google Research Football Multi-agent Scenarios 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 549-570
作者:  Yan Song;  He Jiang;  Zheng Tian;  Haifeng Zhang;  Yingping Zhang;  Jiangcheng Zhu;  Zonghong Dai;  Weinan Zhang;  Jun Wang
Adobe PDF(24588Kb)  |  收藏  |  浏览/下载:0/0  |  提交时间:2024/05/23
Multi-agent reinforcement learning (RL), distributed RL system, population-based training, reward shaping, game theory  
Collective Movement Simulation: Methods and Applications 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 452-480
作者:  Hua Wang;  Xing-Yu Guo;  Hao Tao;  Ming-Liang Xu
Adobe PDF(1439Kb)  |  收藏  |  浏览/下载:0/0  |  提交时间:2024/05/23
Collective movement simulation, multiple objects, multiple discipline, simulation effect, collective intelligence  
Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 411-430
作者:  Qiyue Yin;  Tongtong Yu;  Shengqi Shen;  Jun Yang;  Meijing Zhao;  Wancheng Ni;  Kaiqi Huang;  Bin Liang;  Liang Wang
Adobe PDF(2923Kb)  |  收藏  |  浏览/下载:0/0  |  提交时间:2024/05/23
Deep reinforcement learning, distributed machine learning, self-play, population-play, toolbox  
Effective Model Compression via Stage-wise Pruning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 6, 页码: 937-951
作者:  Ming-Yang Zhang;  Xin-Yi Yu;  Lin-Lin Ou
Adobe PDF(2394Kb)  |  收藏  |  浏览/下载:9/3  |  提交时间:2024/04/23
Automated machine learning (AutoML), channel pruning, model compression, distillation, convolutional neural networks (CNN)  
A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 614-639
作者:  Bolin Gao;  Keke Wan;  Qien Chen;  Zhou Wang;  Rui Li;  Yu Jiang;  Run Mei;  Yinghui Luo;  Keqiang Li
Adobe PDF(12630Kb)  |  收藏  |  浏览/下载:16/5  |  提交时间:2024/04/23
Predictive cruise control (PCC), cloud control system (CCS), cooperative control, efficient operation, intelligent connected vehicle  
A New Diagnosis Method with Few-shot Learning Based on a Class-rebalance Strategy for Scarce Faults in Industrial Processes 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 583-594
作者:  Xinyao Xu;  De Xu;  Fangbo Qin
Adobe PDF(1348Kb)  |  收藏  |  浏览/下载:8/2  |  提交时间:2024/04/23
Data augmentation, feature clustering, class-rebalance strategy, few-shot learning, fault diagnosis  
Federated Learning on Multimodal Data: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 539-553
作者:  Yi-Ming Lin;   Yuan Gao;  Mao-Guo Gong;  Si-Jia Zhang;  Yuan-Qiao Zhang;  Zhi-Yuan Li
Adobe PDF(1253Kb)  |  收藏  |  浏览/下载:11/5  |  提交时间:2024/04/23
Federated learning, multimodal learning, heterogeneous data, edge computing, collaborative learning  
A Survey on Collaborative DNN Inference for Edge Intelligence 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 370-395
作者:  Wei-Qing Ren;  Yu-Ben Qu;  Chao Dong;  Yu-Qian Jing;  Hao Sun;  Qi-Hui Wu;  Song Guo
Adobe PDF(2969Kb)  |  收藏  |  浏览/下载:12/4  |  提交时间:2024/04/23
Artificial intelligence (AI), edge intelligence (EI), distributed computing, deep neural network (DNN), collaborative inference  
Deep Learning-based Moving Object Segmentation: Recent Progress and Research Prospects 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 335-369
作者:  Rui Jiang;  Ruixiang Zhu;  Hu Su;  Yinlin Li;  Yuan Xie;  Wei Zou
Adobe PDF(9061Kb)  |  收藏  |  浏览/下载:7/0  |  提交时间:2024/04/23
Moving object segmentation (MOS), change detection, background subtraction, deep learning (DL), video understanding  
AI in Human-computer Gaming: Techniques, Challenges and Opportunities 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 299-317
作者:  Qi-Yue Yin;  Jun Yang;  Kai-Qi Huang;  Mei-Jing Zhao;  Wan-Cheng Ni;  Bin Liang;  Yan Huang;  Shu Wu;  Liang Wang
Adobe PDF(2608Kb)  |  收藏  |  浏览/下载:17/4  |  提交时间:2024/04/23
Human-computer gaming, AI, intelligent decision making, deep reinforcement learning, self-play