Adaptive Loss Minimization for Semi-Supervised Elastic Embedding
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Feiping Nie | Chris H. Q. Ding | Hua Wang | Heng Huang | C. Ding | Hua Wang | Heng Huang | F. Nie
[1] Feiping Nie,et al. Nonlinear Dimensionality Reduction with Local Spline Embedding , 2009, IEEE Transactions on Knowledge and Data Engineering.
[2] Shannon L. Risacher,et al. Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance , 2011, 2011 International Conference on Computer Vision.
[3] Ivor W. Tsang,et al. Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction , 2010, IEEE Transactions on Image Processing.
[4] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[5] Mikhail Belkin,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..
[6] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[7] Feiping Nie,et al. Efficient and Robust Feature Selection via Joint ℓ2, 1-Norms Minimization , 2010, NIPS.
[8] Chris H. Q. Ding,et al. A learning framework using Green's function and kernel regularization with application to recommender system , 2007, KDD '07.
[9] Feiping Nie,et al. Multi-Class L2,1-Norm Support Vector Machine , 2011, 2011 IEEE 11th International Conference on Data Mining.
[10] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[11] Rynson W. H. Lau,et al. Knowledge and Data Engineering for e-Learning Special Issue of IEEE Transactions on Knowledge and Data Engineering , 2008 .
[12] Thorsten Joachims,et al. Transductive Inference for Text Classification using Support Vector Machines , 1999, ICML.
[13] Zoubin Ghahramani,et al. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.
[14] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[15] Quanquan Gu,et al. Transductive Classification via Dual Regularization , 2009, ECML/PKDD.
[16] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[17] John D. Lafferty,et al. Diffusion Kernels on Graphs and Other Discrete Input Spaces , 2002, ICML.
[18] Tommi S. Jaakkola,et al. Partially labeled classification with Markov random walks , 2001, NIPS.