Hedging Predictions in Machine Learning: The Second Computer Journal Lecture
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[1] David L. Dowe,et al. General Bayesian networks and asymmetric languages , 2003 .
[2] M. Kendall. Theoretical Statistics , 1956, Nature.
[3] J. Mill. A System of Logic , 1843 .
[4] A. Gammerman,et al. Bayesian diagnostic probabilities without assuming independence of symptoms. , 1991, Methods of information in medicine.
[5] Vladimir Vovk,et al. On-line confidence machines are well-calibrated , 2002, The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings..
[6] Edward R. Dougherty,et al. Is cross-validation valid for small-sample microarray classification? , 2004, Bioinform..
[7] Vladimir Vovk,et al. Predictions as Statements and Decisions , 2006, COLT.
[8] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[9] Alexander Gammerman,et al. Qualified predictions for microarray and proteomics pattern diagnostics with confidence machines , 2005, Int. J. Neural Syst..
[10] Harris Papadopoulos,et al. Qualified Prediction for Large Data Sets in the Case of Pattern Recognition , 2002, International Conference on Machine Learning and Applications.
[11] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .
[12] Vladimir Vapnik,et al. Estimation of Dependences Based on Empirical Data: Empirical Inference Science (Information Science and Statistics) , 2006 .
[13] Vladimir Vovk,et al. Comparing the Bayes and Typicalness Frameworks , 2001, ECML.
[14] Céline Rouveirol,et al. Machine Learning: ECML-98 , 1998, Lecture Notes in Computer Science.
[15] Lawrence D. Jackel,et al. Handwritten Digit Recognition with a Back-Propagation Network , 1989, NIPS.
[16] V. Vovk. Competitive On‐line Statistics , 2001 .
[17] A. Dempster. An overview of multivariate data analysis , 1971 .
[18] Péter Gács,et al. Uniform test of algorithmic randomness over a general space , 2003, Theor. Comput. Sci..
[19] G. Shafer. The Unity and Diversity of Probability , 1990 .
[20] A. J. Gammerman,et al. Plant promoter prediction with confidence estimation , 2005, Nucleic acids research.
[21] W. Gasarch,et al. The Book Review Column 1 Coverage Untyped Systems Simple Types Recursive Types Higher-order Systems General Impression 3 Organization, and Contents of the Book , 2022 .
[22] Donald R. Jones,et al. A Taxonomy of Global Optimization Methods Based on Response Surfaces , 2001, J. Glob. Optim..
[23] A. Philip Dawid,et al. Discussion of the Papers by Rissanen and by Wallace and Dowe , 1999, Comput. J..
[24] Vladimir Vapnik,et al. The Nature of Statistical Learning , 1995 .
[25] T. Kuhn,et al. The Structure of Scientific Revolutions. , 1964 .
[26] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[27] Vladimir Vovk,et al. Criterion of calibration for transductive confidence machine with limited feedback , 2006, Theor. Comput. Sci..
[28] Hans-Martin Gutmann,et al. A Radial Basis Function Method for Global Optimization , 2001, J. Glob. Optim..
[29] C. S. Wallace,et al. Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics) , 2005 .
[30] Peter Auer,et al. Using Confidence Bounds for Exploitation-Exploration Trade-offs , 2003, J. Mach. Learn. Res..
[31] K. Popper,et al. Logik der Forschung , 1935 .
[32] J. Sutherland. The Quark and the Jaguar , 1994 .
[33] E. B. Andersen,et al. Information Science and Statistics , 1986 .
[34] Vladimir Cherkassky,et al. The Nature Of Statistical Learning Theory , 1997, IEEE Trans. Neural Networks.
[35] Xiaohui Liu,et al. Consensus clustering and functional interpretation of gene-expression data , 2004, Genome Biology.
[36] Xiaohui Liu,et al. Robust Selection of Predictive Genes via a Simple Classifier , 2006, Applied bioinformatics.
[37] J. Bell,et al. Speakable and Unspeakable in Quatum Mechanics , 1988 .
[38] Ming Li,et al. An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.
[39] David L. Dowe,et al. MML Inference of Oblique Decision Trees , 2004, Australian Conference on Artificial Intelligence.
[40] Vladimir Vovk,et al. Aggregating strategies , 1990, COLT '90.
[41] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[42] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[43] Juyang Weng,et al. Muddy Tasks and the Necessity of Autonomous Mental Development , 2005 .
[44] Alexander Gammerman,et al. Machine-Learning Applications of Algorithmic Randomness , 1999, ICML.
[45] David L. Dowe,et al. Minimum message length and generalized Bayesian nets with asymmetric languages , 2005 .
[46] C. S. Wallace,et al. An Information Measure for Classification , 1968, Comput. J..
[47] Gary James Jason,et al. The Logic of Scientific Discovery , 1988 .
[48] Harris Papadopoulos,et al. Inductive Confidence Machines for Regression , 2002, ECML.
[49] David L. Dowe,et al. Minimum Message Length and Kolmogorov Complexity , 1999, Comput. J..
[50] Per Martin-Löf,et al. The Definition of Random Sequences , 1966, Inf. Control..
[51] A. Zeilinger,et al. Speakable and Unspeakable in Quantum Mechanics , 1989 .
[52] Vladimir Vovk,et al. Ridge Regression Confidence Machine , 2001, International Conference on Machine Learning.
[53] David J. Hand,et al. Classifier Technology and the Illusion of Progress , 2006, math/0606441.
[54] Kevin B. Korb,et al. Calibration and the Evaluation of Predictive Learners , 1999, International Joint Conference on Artificial Intelligence.
[55] Shun-ichi Amari,et al. A Theory of Pattern Recognition , 1968 .