中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共10条，第1-10条 帮助

限定条件                    
已选(0)清除 条数/页：   排序方式：
Generalized Embedding Machines for Recommender Systems 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 571-584
作者:  Enneng Yang;  Xin Xin;  Li Shen;  Yudong Luo;  Guibing Guo
Adobe PDF(1617Kb)  |  收藏  |  浏览/下载：20/9  |  提交时间：2024/05/23
Feature interactions, high-order interaction, factorization machine (FM), recommender system, graph neural network (GNN)  
Ripple Knowledge Graph Convolutional Networks for Recommendation Systems 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 481-494
作者:  Chen Li;  Yang Cao;  Ye Zhu;  Debo Cheng;  Chengyuan Li;  Yasuhiko Morimoto
Adobe PDF(3688Kb)  |  收藏  |  浏览/下载：14/8  |  提交时间：2024/05/23
Deep learning, recommendation systems, knowledge graph, graph convolutional networks (GCNs), graph neural networks (GNNs)  
Parsing Objects at a Finer Granularity: A Survey 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 431-451
作者:  Yifan Zhao;  Jia Li;  Yonghong Tian
Adobe PDF(1743Kb)  |  收藏  |  浏览/下载：8/6  |  提交时间：2024/05/23
Finer granularity, visual parsing, part segmentation, fine-grained object recognition, part relationship  
Asynchronous learning-based output feedback sliding mode control for semi-Markov jumpsystems: A descriptor approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1358-1369
作者:  Zheng Wu;  Yiyun Zhao;  Fanbiao Li;  Tao Yang;  Yang Shi;  Weihua Gui
Adobe PDF(2638Kb)  |  收藏  |  浏览/下载：7/2  |  提交时间：2024/05/22
Asynchronous switching  learning-based control  output feedback  semi-Markovian jump systems  sliding mode control (SMC)  
A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 965-981
作者:  Yong-Chao Li;  Rui-Sheng Jia;  Ying-Xiang Hu;  Hong-Mei Sun
Adobe PDF(10448Kb)  |  收藏  |  浏览/下载：38/17  |  提交时间：2024/03/18
Crowd density estimation  linear feature calibration  vision transformer  weakly-supervision learning  
A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 760-781
作者:  Dingxin He;  HaoPing Wang;  Yang Tian;  Yida Guo
Adobe PDF(9812Kb)  |  收藏  |  浏览/下载：63/13  |  提交时间：2024/02/19
Adaptive control  input deadzone  model-free control  n-DOF upper-limb exoskeleton  neural network  
Fault Estimation for a Class of Markov Jump Piecewise-Affine Systems: Current Feedback Based Iterative Learning Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 418-429
作者:  Yanzheng Zhu;  Nuo Xu;  Fen Wu;  Xinkai Chen;  Donghua Zhou
Adobe PDF(5104Kb)  |  收藏  |  浏览/下载：43/12  |  提交时间：2024/01/23
Current feedback  fault estimation  iterative learning observer  Markov jump piecewise-affine system  
Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 301-328
作者:  Yuchuang Tong;  Haotian Liu;  Zhengtao Zhang
Adobe PDF(7587Kb)  |  收藏  |  浏览/下载：103/22  |  提交时间：2024/01/23
Future trends and challenges  humanoid robots  human-robot interaction  key technologies  potential applications  
Reinforcement Learning in Process Industries: Review and Perspective 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 283-300
作者:  Oguzhan Dogru;  Junyao Xie;  Om Prakash;  Ranjith Chiplunkar;  Jansen Soesanto;  Hongtian Chen;  Kirubakaran Velswamy;  Fadi Ibrahim;  Biao Huang
Adobe PDF(1275Kb)  |  收藏  |  浏览/下载：46/15  |  提交时间：2024/01/23
Process control  process systems engineering  reinforcement learning  
Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 18-36
作者:  Ding Wang;  Ning Gao;  Derong Liu;  Jinna Li;  Frank L. Lewis
Adobe PDF(1945Kb)  |  收藏  |  浏览/下载：263/184  |  提交时间：2024/01/02
Adaptive dynamic programming (ADP)  advanced control  complex environment  data-driven control  event-triggered design  intelligent control  neural networks  nonlinear systems  optimal control  reinforcement learning (RL)