Multilabel Prediction via Cross-View Search
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Weiwei Liu | Ivor W. Tsang | Quan-Sen Sun | Xiaobo Shen | Yew-Soon Ong | I. Tsang | Y. Ong | Quansen Sun | Xiaobo Shen | Weiwei Liu
[1] Robert Krauthgamer,et al. Navigating nets: simple algorithms for proximity search , 2004, SODA '04.
[2] Lin Wu,et al. Unsupervised Metric Fusion Over Multiview Data by Graph Random Walk-Based Cross-View Diffusion , 2017, IEEE Transactions on Neural Networks and Learning Systems.
[3] Zhi-Hua Zhou,et al. ML-KNN: A lazy learning approach to multi-label learning , 2007, Pattern Recognit..
[4] Grigorios Tsoumakas,et al. A Comprehensive Study Over VLAD and Product Quantization in Large-Scale Image Retrieval , 2014, IEEE Transactions on Multimedia.
[5] Wotao Yin,et al. A feasible method for optimization with orthogonality constraints , 2013, Math. Program..
[6] Lin Wu,et al. Robust Hashing for Multi-View Data: Jointly Learning Low-Rank Kernelized Similarity Consensus and Hash Functions , 2016, Image Vis. Comput..
[7] Tommy W. S. Chow,et al. ML-TREE: A Tree-Structure-Based Approach to Multilabel Learning , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[8] Prateek Jain,et al. Sparse Local Embeddings for Extreme Multi-label Classification , 2015, NIPS.
[9] Wei Liu,et al. Supervised Discrete Hashing , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] John Shawe-Taylor,et al. Structural Risk Minimization Over Data-Dependent Hierarchies , 1998, IEEE Trans. Inf. Theory.
[11] Jeff G. Schneider,et al. Multi-Label Output Codes using Canonical Correlation Analysis , 2011, AISTATS.
[12] Wei Liu,et al. Discrete Graph Hashing , 2014, NIPS.
[13] John Langford,et al. Multi-Label Prediction via Compressed Sensing , 2009, NIPS.
[14] Bin Gu,et al. A Robust Regularization Path Algorithm for $\nu $ -Support Vector Classification , 2017, IEEE Transactions on Neural Networks and Learning Systems.
[15] Wei Liu,et al. Learning to Hash for Indexing Big Data—A Survey , 2015, Proceedings of the IEEE.
[16] Lin Wu,et al. Robust Subspace Clustering for Multi-View Data by Exploiting Correlation Consensus , 2015, IEEE Transactions on Image Processing.
[17] Yong Luo,et al. Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification , 2019, IEEE Transactions on Image Processing.
[18] Yong Luo,et al. Manifold Regularized Multitask Learning for Semi-Supervised Multilabel Image Classification , 2013, IEEE Transactions on Image Processing.
[19] Grigorios Tsoumakas,et al. Mining Multi-label Data , 2010, Data Mining and Knowledge Discovery Handbook.
[20] Weiwei Liu,et al. Large Margin Metric Learning for Multi-Label Prediction , 2015, AAAI.
[21] Bin Gu,et al. Incremental Support Vector Learning for Ordinal Regression , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[22] Weiwei Liu,et al. Compressed K-Means for Large-Scale Clustering , 2017, AAAI.
[23] Antonio Torralba,et al. Spectral Hashing , 2008, NIPS.
[24] Aryeh Kontorovich,et al. Maximum Margin Multiclass Nearest Neighbors , 2014, ICML.
[25] Lin Wu,et al. LBMCH: Learning Bridging Mapping for Cross-modal Hashing , 2015, SIGIR.
[26] Piotr Indyk,et al. Similarity Search in High Dimensions via Hashing , 1999, VLDB.
[27] Qing Tian,et al. Cross-heterogeneous-database age estimation through correlation representation learning , 2017, Neurocomputing.
[28] Min-Ling Zhang,et al. A Review on Multi-Label Learning Algorithms , 2014, IEEE Transactions on Knowledge and Data Engineering.
[29] Dale Schuurmans,et al. Multi-label Classification with Output Kernels , 2013, ECML/PKDD.
[30] Yong Luo,et al. Multiview Vector-Valued Manifold Regularization for Multilabel Image Classification , 2013, IEEE Transactions on Neural Networks and Learning Systems.
[31] Weiwei Liu,et al. On the Optimality of Classifier Chain for Multi-label Classification , 2015, NIPS.
[32] Samy Bengio,et al. ADIOS: Architectures Deep In Output Space , 2016, ICML.
[33] Jeff G. Schneider,et al. Maximum Margin Output Coding , 2012, ICML.
[34] Svetlana Lazebnik,et al. Iterative quantization: A procrustean approach to learning binary codes , 2011, CVPR 2011.
[35] Hsuan-Tien Lin,et al. Multilabel Classification with Principal Label Space Transformation , 2012, Neural Computation.
[36] Ivor W. Tsang,et al. Learning with Idealized Kernels , 2003, ICML.
[37] Heng Tao Shen,et al. Semi-Paired Discrete Hashing: Learning Latent Hash Codes for Semi-Paired Cross-View Retrieval , 2017, IEEE Transactions on Cybernetics.
[38] Tat-Seng Chua,et al. NUS-WIDE: a real-world web image database from National University of Singapore , 2009, CIVR '09.
[39] Jieping Ye,et al. Feature extraction via generalized uncorrelated linear discriminant analysis , 2004, ICML.
[40] Xingming Sun,et al. Structural Minimax Probability Machine , 2017, IEEE Transactions on Neural Networks and Learning Systems.
[41] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Hsuan-Tien Lin,et al. Feature-aware Label Space Dimension Reduction for Multi-label Classification , 2012, NIPS.
[43] Weiwei Liu,et al. An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels , 2017, J. Mach. Learn. Res..
[44] Weiwei Liu,et al. Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions , 2017, J. Mach. Learn. Res..
[45] Chih-Jen Lin,et al. LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..
[46] Wei Liu,et al. Classification by Retrieval: Binarizing Data and Classifiers , 2017, SIGIR.
[47] Min Xiao,et al. Cross Language Text Classification via Subspace Co-regularized Multi-view Learning , 2012, ICML.
[48] Tieniu Tan,et al. Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] P. Schönemann,et al. A generalized solution of the orthogonal procrustes problem , 1966 .
[50] Shai Ben-David,et al. Understanding Machine Learning: From Theory to Algorithms , 2014 .
[51] Wotao Yin,et al. A Curvilinear Search Method for p-Harmonic Flows on Spheres , 2009, SIAM J. Imaging Sci..
[52] Mikhail Belkin,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..
[53] Ivor W. Tsang,et al. Core Vector Machines: Fast SVM Training on Very Large Data Sets , 2005, J. Mach. Learn. Res..