Regularization and Semi-supervised Learning on Large Graphs
暂无分享,去创建一个
Mikhail Belkin | Partha Niyogi | Irina Matveeva | Mikhail Belkin | P. Niyogi | Irina Matveeva | M. Belkin
[1] M. Fiedler. Algebraic connectivity of graphs , 1973 .
[2] Luc Devroye,et al. Distribution-free performance bounds for potential function rules , 1979, IEEE Trans. Inf. Theory.
[3] Luc Devroye,et al. Distribution-free inequalities for the deleted and holdout error estimates , 1979, IEEE Trans. Inf. Theory.
[4] Fan Chung,et al. Spectral Graph Theory , 1996 .
[5] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[6] Thorsten Joachims,et al. Transductive Inference for Text Classification using Support Vector Machines , 1999, ICML.
[7] André Elisseeff,et al. Algorithmic Stability and Generalization Performance , 2000, NIPS.
[8] Avrim Blum,et al. Learning from Labeled and Unlabeled Data using Graph Mincuts , 2001, ICML.
[9] Tommi S. Jaakkola,et al. Partially labeled classification with Markov random walks , 2001, NIPS.
[10] Mikhail Belkin,et al. Using Manifold Stucture for Partially Labeled Classification , 2002, NIPS.
[11] John D. Lafferty,et al. Diffusion Kernels on Graphs and Other Discrete Input Spaces , 2002, ICML.
[12] Bernhard Schölkopf,et al. Cluster Kernels for Semi-Supervised Learning , 2002, NIPS.
[13] Éva Tardos,et al. Approximation algorithms for classification problems with pairwise relationships: metric labeling and Markov random fields , 2002, JACM.
[14] Zoubin Ghahramani,et al. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.
[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] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.