Label Propagation and Quadratic Criterion
暂无分享,去创建一个
Alexander Zien | Olivier Chapelle | Bernhard Schölkopf | O. Chapelle | A. Zien | Bernhard Schölkopf
[1] E. Nadaraya. On Estimating Regression , 1964 .
[2] G. S. Watson,et al. Smooth regression analysis , 1964 .
[3] H. J. Scudder,et al. Probability of error of some adaptive pattern-recognition machines , 1965, IEEE Trans. Inf. Theory.
[4] Zoubin Ghahramani,et al. Learning from labeled and unlabeled data with label propagation , 2002 .
[5] S. Rosenberg. The Laplacian on a Riemannian Manifold: The Laplacian on a Riemannian Manifold , 1997 .
[6] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[7] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[8] Thorsten Joachims,et al. Transductive Learning via Spectral Graph Partitioning , 2003, ICML.
[9] Peter G. Doyle,et al. Random Walks and Electric Networks: REFERENCES , 1987 .
[10] Stanley C. Fralick,et al. Learning to recognize patterns without a teacher , 1967, IEEE Trans. Inf. Theory.
[11] Nicolas Le Roux,et al. Efficient Non-Parametric Function Induction in Semi-Supervised Learning , 2004, AISTATS.
[12] Matthias Hein,et al. Measure Based Regularization , 2003, NIPS.
[13] Y. Abu-Mostafa. Machines that Learn from Hints , 1995 .
[14] Yoshua Bengio,et al. Greedy Spectral Embedding , 2005, AISTATS.
[15] Tommi S. Jaakkola,et al. Partially labeled classification with Markov random walks , 2001, NIPS.
[16] Si Wu,et al. Improving support vector machine classifiers by modifying kernel functions , 1999, Neural Networks.
[17] Alexander J. Smola,et al. Learning with non-positive kernels , 2004, ICML.
[18] Elie Bienenstock,et al. Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.
[19] Pascal Vincent,et al. Non-Local Manifold Parzen Windows , 2005, NIPS.
[20] Yoshua Bengio,et al. The Curse of Dimensionality for Local Kernel Machines , 2005 .
[21] Nicolas Le Roux,et al. The Curse of Highly Variable Functions for Local Kernel Machines , 2005, NIPS.
[22] Joachim M. Buhmann,et al. Clustering with the Connectivity Kernel , 2003, NIPS.
[23] ASHOK K. AGRAWALA,et al. Learning with a probabilistic teacher , 1970, IEEE Trans. Inf. Theory.
[24] Mikhail Belkin,et al. Regularization and Semi-supervised Learning on Large Graphs , 2004, COLT.
[25] Yousef Saad,et al. Iterative methods for sparse linear systems , 2003 .
[26] Nicolas Le Roux,et al. Learning Eigenfunctions Links Spectral Embedding and Kernel PCA , 2004, Neural Computation.
[27] Yoshua Bengio,et al. Non-Local Manifold Tangent Learning , 2004, NIPS.