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CASIA OpenIR
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A Unified Framework Based on Graph Consensus Term for Multiview Learning 期刊论文
IEEE Transactions on Neural Networks and Learning Systems, 2022, 卷号: 35, 期号: 3, 页码: 3964 - 3977
作者:  Xiangzhu Meng;  Lin Feng;  Chonghui Guo;  Huibing Wang;  Shu Wu
Adobe PDF(4280Kb)  |  收藏  |  浏览/下载：14/6  |  提交时间：2024/06/21
Disentangled Item Representation for Recommender Systems 期刊论文
Transactions on Intelligent Systems and Technology (TIST), 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Cui Zeyu;  Yu Feng;  Wu Shu;  Liu Qiang;  Wang Liang
Adobe PDF(4552Kb)  |  收藏  |  浏览/下载：225/62  |  提交时间：2021/06/17
Representation learning  Recommender systems  Attribute disentangling  
Multiview Clustering via Unified and View-Specific Embeddings Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 11, 页码: 5541-5553
作者:  Yin, Qiyue;  Wu, Shu;  Wang, Liang
Adobe PDF(2148Kb)  |  收藏  |  浏览/下载：225/5  |  提交时间：2019/10/10
Incomplete multiview data  knowledge graph embedding  multiview learning  subspace learning  
MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation 期刊论文
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018, 期号: no, 页码: no
作者:  Qiang Cui;  Shu Wu;  Qiang Liu;  Wen Zhong;  Liang Wang
Adobe PDF(979Kb)  |  收藏  |  浏览/下载：295/48  |  提交时间：2019/05/09
Multi-view  Sequential Recommendation  Recurrent Neural Network  Cold Start  
Unified subspace learning for incomplete and unlabeled multi-view data 期刊论文
PATTERN RECOGNITION, 2017, 卷号: 67, 期号: 67, 页码: 313-327
作者:  Yin, Qiyue;  Wu, Shu;  Wang, Liang
浏览  |  Adobe PDF(3777Kb)  |  收藏  |  浏览/下载：636/318  |  提交时间：2017/05/10
Multi-view Learning  Subspace Learning  Incomplete And Unlabeled Data  Multi-view Clustering  Cross-modal Retrieval  
Multi-view Clustering via Pairwise Sparse Subspace Representation. Neurocomputing 期刊论文
NEUROCOMPUTING, 2015, 卷号: 156, 期号: 156, 页码: 12-21
作者:  Qiyue Yin;  Shu Wu;  Ran He(赫然);  Liang Wang;  Wu, Shu
浏览  |  Adobe PDF(1292Kb)  |  收藏  |  浏览/下载：390/104  |  提交时间：2015/09/21
Multi-view Clustering  Subspace Clustering  Pairwise Sparse Representation