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2019 | OriginalPaper | Buchkapitel

3. Multi-view Clustering with Partial Information

verfasst von : Zhengming Ding, Handong Zhao, Yun Fu

Erschienen in: Learning Representation for Multi-View Data Analysis

Verlag: Springer International Publishing

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Abstract

Nowadays multi-modal visual data are much easier to access as the technology develops. Nevertheless, there is an underlying problem hidden behind the emerging multi-modality techniques: What if one/more modal data fail? Motivated by this question, we propose an unsupervised method which well handles the incomplete multi-modal data by transforming the original and incomplete data to a new and complete representation in a latent space.

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Literatur
Zurück zum Zitat Bickel S, Scheffer T (2004) Multi-view clustering. In: IEEE international conference on data mining (ICDM) Bickel S, Scheffer T (2004) Multi-view clustering. In: IEEE international conference on data mining (ICDM)
Zurück zum Zitat Blaschko M, Lampert C (2008) Correlational spectral clustering. In: IEEE conference on computer vision and pattern recognition (CVPR) Blaschko M, Lampert C (2008) Correlational spectral clustering. In: IEEE conference on computer vision and pattern recognition (CVPR)
Zurück zum Zitat Cai X, Nie F, Huang H (2013) Multi-view k-means clustering on big data. In: International joint conference on artificial intelligence (IJCAI) Cai X, Nie F, Huang H (2013) Multi-view k-means clustering on big data. In: International joint conference on artificial intelligence (IJCAI)
Zurück zum Zitat Cao X, Zhang C, Fu H, Liu S, Zhang H (2015) Diversity-induced multi-view subspace clustering. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 586–594 Cao X, Zhang C, Fu H, Liu S, Zhang H (2015) Diversity-induced multi-view subspace clustering. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 586–594
Zurück zum Zitat Chaudhuri K, Kakade SM, Livescu K, Sridharan K (2009) Multi-view clustering via canonical correlation analysis. In: International conference on machine learning (ICML), pp 129–136 Chaudhuri K, Kakade SM, Livescu K, Sridharan K (2009) Multi-view clustering via canonical correlation analysis. In: International conference on machine learning (ICML), pp 129–136
Zurück zum Zitat Ding Z, Fu Y (2014) Low-rank common subspace for multi-view learning. In: 2014 IEEE international conference on data mining (ICDM). IEEE, pp 110–119 Ding Z, Fu Y (2014) Low-rank common subspace for multi-view learning. In: 2014 IEEE international conference on data mining (ICDM). IEEE, pp 110–119
Zurück zum Zitat Fred A, Jain A (2005) Combining multiple clusterings using evidence accumulation. IEEE Trans Pattern Anal Mach Intell (TPAMI) 27(6):835–850CrossRef Fred A, Jain A (2005) Combining multiple clusterings using evidence accumulation. IEEE Trans Pattern Anal Mach Intell (TPAMI) 27(6):835–850CrossRef
Zurück zum Zitat Guo X (2015) Robust subspace segmentation by simultaneously learning data representations and their affinity matrix. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence (IJCAI), pp 3547–3553 Guo X (2015) Robust subspace segmentation by simultaneously learning data representations and their affinity matrix. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence (IJCAI), pp 3547–3553
Zurück zum Zitat Huang D, Sun J, Wang Y (2012) The buaa-visnir face database instructions, IRIP-TR-12-FR-001 Huang D, Sun J, Wang Y (2012) The buaa-visnir face database instructions, IRIP-TR-12-FR-001
Zurück zum Zitat Li S, Jiang Y, Zhou Z (2014) Partial multi-view clustering. In: AAAI conference on artificial intelligence (AAAI), pp 1968–1974 Li S, Jiang Y, Zhou Z (2014) Partial multi-view clustering. In: AAAI conference on artificial intelligence (AAAI), pp 1968–1974
Zurück zum Zitat Lin Z, Liu R, Su Z (2011) Linearized alternating direction method with adaptive penalty for low-rank representation. In: Neural information processing systems (NIPS), pp 612–620 Lin Z, Liu R, Su Z (2011) Linearized alternating direction method with adaptive penalty for low-rank representation. In: Neural information processing systems (NIPS), pp 612–620
Zurück zum Zitat Liu J, Wang C, Gao J, Han J (2013) Multi-view clustering via joint nonnegative matrix factorization. In: SIAM international conference on data mining (SDM), pp 252–260CrossRef Liu J, Wang C, Gao J, Han J (2013) Multi-view clustering via joint nonnegative matrix factorization. In: SIAM international conference on data mining (SDM), pp 252–260CrossRef
Zurück zum Zitat Lu C, Min H, Zhao Z, Zhu L, Huang D, Yan S (2012) Robust and efficient subspace segmentation via least squares regression. In: European conference on computer vision (ECCV), pp 347–360CrossRef Lu C, Min H, Zhao Z, Zhu L, Huang D, Yan S (2012) Robust and efficient subspace segmentation via least squares regression. In: European conference on computer vision (ECCV), pp 347–360CrossRef
Zurück zum Zitat Oreifej O, Liu Z (2013) HON4D: histogram of oriented 4d normals for activity recognition from depth sequences. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 716–723 Oreifej O, Liu Z (2013) HON4D: histogram of oriented 4d normals for activity recognition from depth sequences. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 716–723
Zurück zum Zitat Shao W, He L, Yu PS (2015) Multiple incomplete views clustering via weighted nonnegative matrix factorization with \(l_{2, 1}\) regularization. In: Machine learning and knowledge discovery in databases - European conference, ECML PKDD, pp 318–334 Shao W, He L, Yu PS (2015) Multiple incomplete views clustering via weighted nonnegative matrix factorization with \(l_{2, 1}\) regularization. In: Machine learning and knowledge discovery in databases - European conference, ECML PKDD, pp 318–334
Zurück zum Zitat Singh A, Gordon G (2008) Relational learning via collective matrix factorization. In: ACM SIGKDD international conference on knowledge discovery and data mining (KDD), pp 650–658 Singh A, Gordon G (2008) Relational learning via collective matrix factorization. In: ACM SIGKDD international conference on knowledge discovery and data mining (KDD), pp 650–658
Zurück zum Zitat Wang J, Liu Z, Wu Y, Yuan J (2012) Mining actionlet ensemble for action recognition with depth cameras. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 1290–1297 Wang J, Liu Z, Wu Y, Yuan J (2012) Mining actionlet ensemble for action recognition with depth cameras. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 1290–1297
Zurück zum Zitat Zhang C, Fu H, Liu S, Liu G, Cao X (2015) Low-rank tensor constrained multiview subspace clustering. In: 2015 IEEE international conference on computer vision (ICCV), pp 1582–1590 Zhang C, Fu H, Liu S, Liu G, Cao X (2015) Low-rank tensor constrained multiview subspace clustering. In: 2015 IEEE international conference on computer vision (ICCV), pp 1582–1590
Zurück zum Zitat Zhao H, Fu Y (2015) Dual-regularized multi-view outlier detection. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence, (IJCAI), pp 4077–4083 Zhao H, Fu Y (2015) Dual-regularized multi-view outlier detection. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence, (IJCAI), pp 4077–4083
Metadaten
Titel
Multi-view Clustering with Partial Information
verfasst von
Zhengming Ding
Handong Zhao
Yun Fu
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-00734-8_3