Multi-view clustering by joint spectral embedding and spectral rotation

Abstract Discrete Spectral clustering is an effective tool for directly getting discrete labels. However, existing spectral clustering carry out spectral embedding and spectral rotation separately, which may limit their clustering performance. Seamlessly connecting above two processes is challenging. In this paper, we propose a new multi-view clustering framework, namely Multi-view Clustering by Joint Spectral Embedding and Spectral Rotation. In the framework, the differences of Laplacian matrices from different views are learned adaptively. Moreover, the real-valued cluster indicator matrix is approximated by continuous orthogonalization of the discrete clustering index matrix. By doing so, our method has better convergence, which is also strictly mathematically proven. Extensive experiments indicate that our method is superior to several state-of-the-art methods. Our code will be available at XXXX.

[1]  Ying Liang,et al.  Multi-view projected clustering with graph learning , 2020, Neural Networks.

[2]  Changsheng Xu,et al.  Cross-Domain Feature Learning in Multimedia , 2015, IEEE Transactions on Multimedia.

[3]  Qianqian Wang,et al.  Multi-view clustering by joint manifold learning and tensor nuclear norm , 2020, Neurocomputing.

[4]  Feiping Nie,et al.  Large-Scale Multi-View Spectral Clustering via Bipartite Graph , 2015, AAAI.

[5]  Tommy W. S. Chow,et al.  Tree2Vector: Learning a Vectorial Representation for Tree-Structured Data , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[6]  Feiping Nie,et al.  Multi-Modal Joint Clustering With Application for Unsupervised Attribute Discovery , 2018, IEEE Transactions on Image Processing.

[7]  Xuelong Li,et al.  Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification , 2016, IJCAI.

[8]  Lei Du,et al.  Robust Multi-View Spectral Clustering via Low-Rank and Sparse Decomposition , 2014, AAAI.

[9]  Xuelong Li,et al.  Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours , 2017, AAAI.

[10]  Changsheng Xu,et al.  Learning Consistent Feature Representation for Cross-Modal Multimedia Retrieval , 2015, IEEE Transactions on Multimedia.

[11]  Tat-Seng Chua,et al.  NUS-WIDE: a real-world web image database from National University of Singapore , 2009, CIVR '09.

[12]  Xinbo Gao,et al.  Multiview Subspace Clustering by an Enhanced Tensor Nuclear Norm , 2021, IEEE Transactions on Cybernetics.

[13]  Kun Zhan,et al.  Graph Learning for Multiview Clustering , 2018, IEEE Transactions on Cybernetics.

[14]  Hal Daumé,et al.  Co-regularized Multi-view Spectral Clustering , 2011, NIPS.

[15]  Jianbo Shi,et al.  Multiclass spectral clustering , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[16]  Jiancheng Lv,et al.  Multi-view Spectral Clustering Network , 2019, IJCAI.

[17]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[18]  Xuelong Li,et al.  Spectral Clustering by Joint Spectral Embedding and Spectral Rotation , 2020, IEEE Transactions on Cybernetics.

[19]  Pietro Perona,et al.  Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[20]  Feiping Nie,et al.  Angle 2DPCA: A New Formulation for 2DPCA , 2018, IEEE Transactions on Cybernetics.

[21]  Feiping Nie,et al.  Spectral Rotation versus K-Means in Spectral Clustering , 2013, AAAI.

[22]  Xuelong Li,et al.  A generalized power iteration method for solving quadratic problem on the Stiefel manifold , 2017, Science China Information Sciences.

[23]  Xinbo Gao,et al.  Self-Supervised Graph Convolutional Network for Multi-View Clustering , 2021, IEEE Transactions on Multimedia.

[24]  Zi Huang,et al.  A Unified Framework for Discrete Spectral Clustering , 2016, IJCAI.

[25]  Zhaoyang Li,et al.  Deep Adversarial Multi-view Clustering Network , 2019, IJCAI.

[26]  Xiangdong Zhang,et al.  Low-rank tensor constrained co-regularized multi-view spectral clustering , 2020, Neural Networks.

[27]  Hong Liu,et al.  Incomplete Multiview Spectral Clustering With Adaptive Graph Learning , 2020, IEEE Transactions on Cybernetics.

[28]  Xuelong Li,et al.  Multiview Clustering via Adaptively Weighted Procrustes , 2018, KDD.

[29]  Xinbo Gao,et al.  Self-representation and Class-Specificity Distribution Based Multi-View Clustering , 2021, Neurocomputing.

[30]  Xinbo Gao,et al.  Multiview Clustering by Joint Latent Representation and Similarity Learning , 2020, IEEE Transactions on Cybernetics.

[31]  Nebojsa Jojic,et al.  LOCUS: learning object classes with unsupervised segmentation , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[32]  Xuelong Li,et al.  Multi-view Subspace Clustering , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).