Sparse Bayesian Learning and the Relevance Vector Machine (2001)

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by Michael E. Tipping , Alex Smola
Citations:551 - 5 self

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Bayesian Approach To Support Vector Machines – Chu Wei - 2003
373 An introduction to kernel-based learning algorithms – Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf - 2001
42 Moderating the Outputs of Support Vector Machine Classifiers – James Tin-yau Kwok - 1999
38 Adaptive Sparseness Using Jeffreys Prior – Mário A. T. Figueiredo - 2001
24 Bayesian learning of sparse classifiers – Mário A. T. Figueiredo, Anil K. Jain - 2001
14 Bayesian Regression and Classification – Christopher M. Bishop - 2003
473 A tutorial on support vector regression – Alex J. Smola, Bernhard Schölkopf - 2004
80 Adaptive Sparseness for Supervised Learning – Mario A.T. Figueiredo, Senior Member - 2003
4 Bayesian kernel methods – Alexander J. Smola, Bernhard Schölkopf - 2003
19 Sollich P: Model Selection for Support Vector Machine Classification. Neurocomputing 2003 – Carl Gold, Peter Sollich
1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
Algorithms and Representations for Reinforcement Learning – unknown authors
62 The Kernel Recursive Least Squares Algorithm – Yaakov Engel, Shie Mannor, Ron Meir - 2003
37 Algorithms and Representations for Reinforcement Learning – Yaakov Engel, Douglas Adams - 2005
44 Bayesian methods for support vector machines: Evidence and predictive class probabilities – Peter Sollich - 2002
2272 A tutorial on support vector machines for pattern recognition – Christopher J. C. Burges - 1998
2 Probabilistic Classification Vector Machines – Huanhuan Chen, Peter Tiňo, Xin Yao
On the Use of Advanced Inductive Methods for Knowledge Extraction from Complex Datasets – Jaz S. Kandola, Steve R. Gunn, Ian Sinclair, Philippa Reed - 1999
165 Learning with Labeled and Unlabeled Data – Matthias Seeger - 2001