A game of prediction with expert advice
暂无分享,去创建一个
[1] Feller William,et al. An Introduction To Probability Theory And Its Applications , 1950 .
[2] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .
[3] Gérard D. Cohen,et al. A nonconstructive upper bound on covering radius , 1983, IEEE Trans. Inf. Theory.
[4] J. Rissanen. A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH , 1983 .
[5] A. P. Dawid,et al. Present position and potential developments: some personal views , 1984 .
[6] N. Littlestone. Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).
[7] Alfredo De Santis,et al. Learning probabilistic prediction functions , 1988, [Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science.
[8] Donald A. Martin,et al. An Extension of Borel Determinacy , 1990, Ann. Pure Appl. Log..
[9] Vladimir Vovk,et al. Aggregating strategies , 1990, COLT '90.
[10] David Williams,et al. Probability with Martingales , 1991, Cambridge mathematical textbooks.
[11] Dean Phillips Foster. Prediction in the Worst Case , 1991 .
[12] Philip M. Long,et al. On-line learning of linear functions , 1991, STOC '91.
[13] Vladimir Vovk,et al. Universal Forecasting Algorithms , 1992, Inf. Comput..
[14] David Haussler,et al. How to use expert advice , 1993, STOC.
[15] Dean P. Foster,et al. A Randomization Rule for Selecting Forecasts , 1993, Oper. Res..
[16] Philip M. Long,et al. On-line learning with linear loss constraints , 1993, COLT '93.
[17] Manfred K. Warmuth,et al. The Weighted Majority Algorithm , 1994, Inf. Comput..
[18] David Haussler,et al. Tight worst-case loss bounds for predicting with expert advice , 1994, EuroCOLT.
[19] Ray J. Solomonoff. The discovery of algorithmic probability: A guide for the programming of true creativity , 1995, EuroCOLT.
[20] Kenji Yamanishi. Randomized approximate aggregating strategies and their applications to prediction and discrimination , 1995, COLT '95.
[21] Mark Herbster,et al. Tracking the Best Expert , 1995, Machine-mediated learning.
[22] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[23] Erik Ordentlich,et al. Universal portfolios with side information , 1996, IEEE Trans. Inf. Theory.
[24] Yoav Freund,et al. Predicting a binary sequence almost as well as the optimal biased coin , 2003, COLT '96.
[25] Alexander Gammerman,et al. Computational Learning and Probabilistic Reasoning , 1996 .
[26] Yoram Singer,et al. On‐Line Portfolio Selection Using Multiplicative Updates , 1998, ICML.
[27] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[28] Charles M. Grinstead,et al. Introduction to probability , 1999, Statistics for the Behavioural Sciences.
[29] Manfred K. Warmuth,et al. Exponentiated Gradient Versus Gradient Descent for Linear Predictors , 1997, Inf. Comput..
[30] Vladimir Cherkassky,et al. The Nature Of Statistical Learning Theory , 1997, IEEE Trans. Neural Networks.