Vladimir Vovk is Professor of Computer Science at Royal Holloway, University of London; he also heads the Computer Learning Research Centre. His research interests include machine learning; predictive and Kolmogorov complexity, randomness, and information; the foundations of probability and statistics. He has published numerous research papers in these fields and two books: "Probability and finance: It's only a game" (with Glenn Shafer, Wiley, New York, 2001; Japanese translation: Iwanami Shoten, Tokyo, 2006) and "Algorithmic learning in a random world" (with Alex Gammerman and Glenn Shafer, Springer, New York, 2005), which is a comprehensive book on the Conformal Predictions framework.
Télécharger le livre :  Algorithmic Learning in a Random World

This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature of conformal prediction is the principled treatment of the reliability of predictions. The prediction algorithms...
Editeur : Springer
Parution : 2022-12-13

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168,79

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Télécharger le livre :  Game-Theoretic Foundations for Probability and Finance

Game-theoretic probability and finance come of age Glenn Shafer and Vladimir Vovk’s Probability and Finance, published in 2001, showed that perfect-information games can be used to define mathematical probability. Based on fifteen years of further research,...
Editeur : Wiley
Parution : 2019-05-08
Collection : Wiley Series in Probability and Statistics
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117,05

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Télécharger le livre :  Measures of Complexity

This book brings together historical notes, reviews of research developments, fresh ideas on how to make VC (Vapnik–Chervonenkis) guarantees tighter, and new technical contributions in the areas of machine learning, statistical inference, classification, algorithmic...
Editeur : Springer
Parution : 2015-09-03

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94,94

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Télécharger le livre :  Conformal Prediction for Reliable Machine Learning

The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face...
Editeur : Morgan Kaufmann
Parution : 2014-04-23

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95,95

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Télécharger le livre :  Empirical Inference

This book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical...
Editeur : Springer
Parution : 2013-12-11

Format(s) : ePub
52,74

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Télécharger le livre :  Algorithmic Learning in a Random World

Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been...
Editeur : Springer
Parution : 2005-12-05

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