|
|
Bayesian Approach To Support Vector Machines
– Chu Wei
- 2003
|
|
279
|
An introduction to kernel-based learning algorithms
– Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf
- 2001
|
|
36
|
Moderating the Outputs of Support Vector Machine Classifiers
– James Tin-yau Kwok
- 1999
|
|
29
|
Adaptive Sparseness Using Jeffreys Prior
– Mário A. T. Figueiredo
- 2001
|
|
21
|
Bayesian learning of sparse classifiers
– Mário A. T. Figueiredo, Anil K. Jain
- 2001
|
|
7
|
Bayesian Regression and Classification
– Christopher M. Bishop
- 2003
|
|
57
|
Adaptive Sparseness for Supervised Learning
– Mario A.T. Figueiredo, Senior Member
- 2003
|
|
2
|
Bayesian kernel methods
– Alexander J. Smola, Bernhard Schölkopf
- 2003
|
|
1
|
A review of RKHS methods in machine learning
– Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola
- 2006
|
|
17
|
Model Selection for Support Vector Machine Classification
– Carl Gold, Peter Sollich
- 2002
|
|
|
Algorithms and Representations for Reinforcement Learning
– unknown authors
|
|
22
|
Algorithms and Representations for Reinforcement Learning
– Yaakov Engel, Douglas Adams
- 2005
|
|
37
|
The Kernel Recursive Least Squares Algorithm
– Yaakov Engel, Shie Mannor, Ron Meir
- 2003
|
|
40
|
Bayesian methods for support vector machines: Evidence and predictive class probabilities
– Peter Sollich
- 2002
|
|
1656
|
A tutorial on support vector machines for pattern recognition
– Christopher J. C. Burges
- 1998
|
|
308
|
A tutorial on support vector regression
– Alex J. Smola, Bernhard Schölkopf
- 2004
|
|
1
|
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
|
|
134
|
Learning with Labeled and Unlabeled Data
– Matthias Seeger
- 2001
|
