High-Order Distance-Based Multiview Stochastic Learning in Image Classification
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Yuan Yan Tang | Jun Yu | Dacheng Tao | Yong Rui | Y. Rui | D. Tao | Yuanyan Tang | Jun Yu
[1] H. Hotelling. Analysis of a complex of statistical variables into principal components. , 1933 .
[2] R. Fisher. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .
[3] Marc Rioux,et al. Recognition and Shape Synthesis of 3-D Objects Based on Attributed Hypergraphs , 1989, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[5] Andrew B. Kahng,et al. Recent directions in netlist partitioning: a survey , 1995, Integr..
[6] Tomaso A. Poggio,et al. Regularization Theory and Neural Networks Architectures , 1995, Neural Computation.
[7] David G. Lowe,et al. Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[8] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[9] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[10] Geoffrey E. Hinton,et al. Stochastic Neighbor Embedding , 2002, NIPS.
[11] Mikhail Belkin,et al. Using manifold structure for partially labelled classification , 2002, NIPS 2002.
[12] Bernhard Schölkopf,et al. Cluster Kernels for Semi-Supervised Learning , 2002, NIPS.
[13] Zoubin Ghahramani,et al. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.
[14] Rong Yan,et al. The combination limit in multimedia retrieval , 2003, MULTIMEDIA '03.
[15] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[16] Alexander J. Smola,et al. Kernels and Regularization on Graphs , 2003, COLT.
[17] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[18] Harriet J. Nock,et al. Discriminative model fusion for semantic concept detection and annotation in video , 2003, ACM Multimedia.
[19] Antonio Torralba,et al. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.
[20] Edward Y. Chang,et al. Optimal multimodal fusion for multimedia data analysis , 2004, MULTIMEDIA '04.
[21] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[22] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.
[23] Erik G. Learned-Miller,et al. Learning Hyper-Features for Visual Identification , 2004, NIPS.
[24] Antonio Criminisi,et al. Object categorization by learned universal visual dictionary , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[25] Erik G. Learned-Miller,et al. Building a classification cascade for visual identification from one example , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[26] Cees G. M. Snoek,et al. Early versus late fusion in semantic video analysis , 2005, MULTIMEDIA '05.
[27] Pietro Perona,et al. Learning object categories from Google's image search , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[28] Yurii Nesterov,et al. Smooth minimization of non-smooth functions , 2005, Math. Program..
[29] Lior Rokach,et al. Top-down induction of decision trees classifiers - a survey , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[30] Jianguo Zhang,et al. The PASCAL Visual Object Classes Challenge , 2006 .
[31] Mikhail Belkin,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..
[32] Alexander Zien,et al. Semi-Supervised Learning , 2006 .
[33] Serge J. Belongie,et al. Higher order learning with graphs , 2006, ICML.
[34] Bernhard Schölkopf,et al. Learning with Hypergraphs: Clustering, Classification, and Embedding , 2006, NIPS.
[35] Jitendra Malik,et al. Image Retrieval and Classification Using Local Distance Functions , 2006, NIPS.
[36] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[37] Jieping Ye,et al. Hypergraph spectral learning for multi-label classification , 2008, KDD.
[38] S. Sathiya Keerthi,et al. Optimization Techniques for Semi-Supervised Support Vector Machines , 2008, J. Mach. Learn. Res..
[39] Amnon Shashua,et al. Probabilistic graph and hypergraph matching , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[40] Jieping Ye,et al. An accelerated gradient method for trace norm minimization , 2009, ICML '09.
[41] Dimitris N. Metaxas,et al. ]Video object segmentation by hypergraph cut , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[42] TaeHyun Hwang,et al. A hypergraph-based learning algorithm for classifying gene expression and arrayCGH data with prior knowledge , 2009, Bioinform..
[43] Xian-Sheng Hua,et al. Ensemble Manifold Regularization , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Chun Chen,et al. Music recommendation by unified hypergraph: combining social media information and music content , 2010, ACM Multimedia.
[45] Francesca Bovolo,et al. A Novel Technique for Subpixel Image Classification Based on Support Vector Machine , 2010, IEEE Transactions on Image Processing.
[46] Qingshan Liu,et al. Image retrieval via probabilistic hypergraph ranking , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[47] Yongdong Zhang,et al. Multiview Spectral Embedding , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[48] Yihong Gong,et al. Unsupervised Image Categorization by Hypergraph Partition , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] Jun Yu,et al. Complex Object Correspondence Construction in Two-Dimensional Animation , 2011, IEEE Transactions on Image Processing.
[50] Xingquan Zhu. Cross-Domain Semi-Supervised Learning Using Feature Formulation. , 2011, IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society.
[51] Fei Wang,et al. Semisupervised Metric Learning by Maximizing Constraint Margin , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[52] Jun Yu,et al. On Combining Multiple Features for Cartoon Character Retrieval and Clip Synthesis , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[53] Meng Wang,et al. Adaptive Hypergraph Learning and its Application in Image Classification , 2012, IEEE Transactions on Image Processing.
[54] Meng Wang,et al. Semisupervised Multiview Distance Metric Learning for Cartoon Synthesis , 2012, IEEE Transactions on Image Processing.
[55] Gang Wang,et al. Solution Path for Manifold Regularized Semisupervised Classification , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[56] Meng Wang,et al. Multimodal Graph-Based Reranking for Web Image Search , 2012, IEEE Transactions on Image Processing.
[57] Dacheng Tao,et al. A Survey on Multi-view Learning , 2013, ArXiv.
[58] Xuelong Li,et al. Rank Preserving Sparse Learning for Kinect Based Scene Classification , 2013, IEEE Transactions on Cybernetics.
[59] Jun Yu,et al. Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research , 2013 .
[60] Xuelong Li,et al. Hessian Regularized Support Vector Machines for Mobile Image Annotation on the Cloud , 2013, IEEE Transactions on Multimedia.
[61] Jun Yu,et al. Exploiting Click Constraints and Multi-view Features for Image Re-ranking , 2014, IEEE Transactions on Multimedia.
[62] Jun Yu,et al. Semantic preserving distance metric learning and applications , 2014, Inf. Sci..