Discussion on hedging predictions in machine learning by A Gammerman and V Vovk

[1]  Péter Gács,et al.  Uniform test of algorithmic randomness over a general space , 2003, Theor. Comput. Sci..

[2]  Harris Papadopoulos,et al.  Inductive Confidence Machines for Regression , 2002, ECML.

[3]  G. Shafer The Unity and Diversity of Probability , 1990 .

[4]  David L. Dowe,et al.  Minimum Message Length and Kolmogorov Complexity , 1999, Comput. J..

[5]  Donald R. Jones,et al.  A Taxonomy of Global Optimization Methods Based on Response Surfaces , 2001, J. Glob. Optim..

[6]  A. Philip Dawid,et al.  Discussion of the Papers by Rissanen and by Wallace and Dowe , 1999, Comput. J..

[7]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[8]  Hans-Martin Gutmann,et al.  A Radial Basis Function Method for Global Optimization , 2001, J. Glob. Optim..

[9]  Edward R. Dougherty,et al.  Is cross-validation valid for small-sample microarray classification? , 2004, Bioinform..

[10]  Xiaohui Liu,et al.  Consensus clustering and functional interpretation of gene-expression data , 2004, Genome Biology.

[11]  Xiaohui Liu,et al.  Robust Selection of Predictive Genes via a Simple Classifier , 2006, Applied bioinformatics.

[12]  A. Dempster An overview of multivariate data analysis , 1971 .

[13]  Alexander Gammerman,et al.  Hedging Predictions in Machine Learning: The Second Computer Journal Lecture , 2006, Comput. J..

[14]  C. S. Wallace,et al.  An Information Measure for Classification , 1968, Comput. J..

[15]  David J. Hand,et al.  Classifier Technology and the Illusion of Progress , 2006, math/0606441.

[16]  Vladimir Vovk,et al.  Predictions as Statements and Decisions , 2006, COLT.