Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification
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[1] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[2] Jiawei Han,et al. Non-negative Matrix Factorization on Manifold , 2008, 2008 Eighth IEEE International Conference on Data Mining.
[3] Thomas G. Dietterich,et al. Improving SVM accuracy by training on auxiliary data sources , 2004, ICML.
[4] Inderjit S. Dhillon,et al. Semi-supervised graph clustering: a kernel approach , 2005, ICML '05.
[5] Claire Cardie,et al. Constrained K-means Clustering with Background Knowledge , 2001, ICML.
[6] Rajat Raina,et al. Self-taught learning: transfer learning from unlabeled data , 2007, ICML '07.
[7] Qiang Yang,et al. Boosting for transfer learning , 2007, ICML '07.
[8] Inderjit S. Dhillon,et al. Co-clustering documents and words using bipartite spectral graph partitioning , 2001, KDD '01.
[9] Charles A. Micchelli,et al. Kernels for Multi--task Learning , 2004, NIPS.
[10] Rich Caruana,et al. Multitask Learning , 1997, Machine-mediated learning.
[11] Qiang Yang,et al. Co-clustering based classification for out-of-domain documents , 2007, KDD '07.
[12] Yizhou Sun,et al. Heterogeneous source consensus learning via decision propagation and negotiation , 2009, KDD.
[13] Quanquan Gu,et al. Local Learning Regularized Nonnegative Matrix Factorization , 2009, IJCAI.
[14] Tao Li,et al. Document clustering via adaptive subspace iteration , 2004, SIGIR '04.
[15] Chris H. Q. Ding,et al. Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[16] Thorsten Joachims,et al. Transductive Inference for Text Classification using Support Vector Machines , 1999, ICML.
[17] Massimiliano Pontil,et al. Regularized multi--task learning , 2004, KDD.
[18] Jieping Ye,et al. A convex formulation for learning shared structures from multiple tasks , 2009, ICML '09.
[19] Inderjit S. Dhillon,et al. Information-theoretic co-clustering , 2003, KDD '03.
[20] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[21] Qiang Yang,et al. Self-taught clustering , 2008, ICML '08.
[22] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[23] Chris H. Q. Ding,et al. Convex and Semi-Nonnegative Matrix Factorizations , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[24] Tong Zhang,et al. A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , 2005, J. Mach. Learn. Res..
[25] Quanquan Gu,et al. Co-clustering on manifolds , 2009, KDD.
[26] Qiang Yang,et al. Transfer Learning via Dimensionality Reduction , 2008, AAAI.
[27] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[28] Jiawei Han,et al. Knowledge transfer via multiple model local structure mapping , 2008, KDD.
[29] Lawrence Carin,et al. Logistic regression with an auxiliary data source , 2005, ICML.
[30] Zoubin Ghahramani,et al. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.
[31] Chris H. Q. Ding,et al. Orthogonal nonnegative matrix t-factorizations for clustering , 2006, KDD '06.
[32] Fei Wang,et al. Semi-Supervised Clustering via Matrix Factorization , 2008, SDM.
[33] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[34] Chih-Jen Lin,et al. Working Set Selection Using Second Order Information for Training Support Vector Machines , 2005, J. Mach. Learn. Res..
[35] Massimiliano Pontil,et al. Multi-Task Feature Learning , 2006, NIPS.
[36] Qiang Yang,et al. Spectral domain-transfer learning , 2008, KDD.
[37] Qiang Yang,et al. EigenTransfer: a unified framework for transfer learning , 2009, ICML '09.
[38] Raymond J. Mooney,et al. A probabilistic framework for semi-supervised clustering , 2004, KDD.
[39] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.