Leading strategies in competitive on-line prediction
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[1] Vladimir Vovk. Defensive Prediction with Expert Advice , 2005, ALT.
[2] Manfred K. Warmuth,et al. Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions , 1999, Machine Learning.
[3] G. Shafer,et al. Probability and Finance: It's Only a Game! , 2001 .
[4] Akimichi Takemura,et al. Defensive Forecasting for Linear Protocols , 2005, ALT.
[5] Philip M. Long,et al. Worst-case quadratic loss bounds for prediction using linear functions and gradient descent , 1996, IEEE Trans. Neural Networks.
[6] C. Schnorr. Zufälligkeit und Wahrscheinlichkeit , 1971 .
[7] Manfred K. Warmuth,et al. Relative Loss Bounds for Multidimensional Regression Problems , 1997, Machine Learning.
[8] A. P. Dawid,et al. Probability, Causality and the Empirical World: A Bayes-de Finetti-Popper-Borel Synthesis , 2004 .
[9] László Györfi,et al. A Probabilistic Theory of Pattern Recognition , 1996, Stochastic Modelling and Applied Probability.
[10] Claudio Gentile,et al. Adaptive and Self-Confident On-Line Learning Algorithms , 2000, J. Comput. Syst. Sci..
[11] Vladimir Vovk,et al. Competing with Stationary Prediction Strategies , 2006, COLT.
[12] Mark Herbster,et al. Tracking the Best Linear Predictor , 2001, J. Mach. Learn. Res..
[13] L. Bregman. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming , 1967 .
[14] M. Kendall. Theoretical Statistics , 1956, Nature.
[15] Manfred K. Warmuth,et al. Relative loss bounds for single neurons , 1999, IEEE Trans. Neural Networks.
[16] Vladimir Vovk,et al. Competing with Markov prediction strategies , 2006, ArXiv.
[17] Vladimir Vovk,et al. Predictions as Statements and Decisions , 2006, COLT.
[18] N. Aronszajn. Theory of Reproducing Kernels. , 1950 .
[19] Jean-Luc Ville. Étude critique de la notion de collectif , 1939 .
[20] Vladimir Vovk. Competing with Wild Prediction Rules , 2006, COLT.
[21] S. Saitoh. Integral Transforms, Reproducing Kernels and Their Applications , 1997 .
[22] Vladimir Vovk,et al. On-Line Regression Competitive with Reproducing Kernel Hilbert Spaces , 2005, TAMC.
[23] Philip M. Long,et al. WORST-CASE QUADRATIC LOSS BOUNDS FOR ON-LINE PREDICTION OF LINEAR FUNCTIONS BY GRADIENT DESCENT , 1993 .
[24] Patrick Brézillon,et al. Lecture Notes in Artificial Intelligence , 1999 .
[25] Par N. Aronszajn. La théorie des noyaux reproduisants et ses applications Première Partie , 1943, Mathematical Proceedings of the Cambridge Philosophical Society.
[26] J. Ellul. The Technological Bluff , 1990 .
[27] Akimichi Takemura,et al. Defensive Forecasting , 2005, AISTATS.
[28] Vladimir Vovk. Competitive on-line learning with a convex loss function , 2005, ArXiv.
[29] A. P. Dawid,et al. Present position and potential developments: some personal views , 1984 .
[30] Vladimir Vovk. Non-asymptotic calibration and resolution , 2007, Theor. Comput. Sci..
[31] Don R. Hush,et al. Function Classes That Approximate the Bayes Risk , 2006, COLT.
[32] 齋藤 三郎. Integral transforms, reproducing kernels and their applications , 1997 .
[33] Per Martin-Löf,et al. The Definition of Random Sequences , 1966, Inf. Control..
[34] R Š Lipcer,et al. ON THE QUESTION OF ABSOLUTE CONTINUITY AND SINGULARITY OF PROBABILITY MEASURES , 1977 .
[35] A. Dawid. Calibration-Based Empirical Probability , 1985 .
[36] Vladimir Vovk,et al. Competing with wild prediction rules , 2005, Machine Learning.
[37] Vladimir Vovk. Probability theory for the Brier game , 2001, Theor. Comput. Sci..
[38] Ray J. Solomonoff,et al. Complexity-based induction systems: Comparisons and convergence theorems , 1978, IEEE Trans. Inf. Theory.
[39] Vladimir Vovk. Leading Strategies in Competitive On-Line Prediction , 2006, ALT.
[40] D. Blackwell,et al. Merging of Opinions with Increasing Information , 1962 .
[41] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .