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Measures of complexityfestschrift fo...

Chervonenkis, Alexey.

Measures of complexityfestschrift for Alexey Chervonenkis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Measures of complexityedited by Vladimir Vovk, Harris Papadopoulos, Alexander Gammerman.
Reminder of title:	festschrift for Alexey Chervonenkis /
other author:	Chervonenkis, Alexey.
Published:	Cham :Springer International Publishing :2015.
Description:	xxxi, 399 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning.
Online resource:	http://dx.doi.org/10.1007/978-3-319-21852-6
ISBN:	9783319218526$q(electronic bk.)

Measures of complexityfestschrift for Alexey Chervonenkis /
Measures of complexityfestschrift for Alexey Chervonenkis /[electronic resource] :edited by Vladimir Vovk, Harris Papadopoulos, Alexander Gammerman. - Cham :Springer International Publishing :2015. - xxxi, 399 p. :ill., digital ;24 cm.

Chervonenkis's Recollections -- A Paper That Created Three New Fields -- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities -- Sketched History: VC Combinatorics, 1826 up to 1975 -- Institute of Control Sciences through the Lens of VC Dimension -- VC Dimension, Fat-Shattering Dimension, Rademacher Averages, and Their Applications -- Around Kolmogorov Complexity: Basic Notions and Results -- Predictive Complexity for Games with Finite Outcome Spaces -- Making Vapnik-Chervonenkis Bounds Accurate -- Comment: Transductive PAC-Bayes Bounds Seen as a Generalization of Vapnik-Chervonenkis Bounds -- Comment: The Two Styles of VC Bounds -- Rejoinder: Making VC Bounds Accurate -- Measures of Complexity in the Theory of Machine Learning -- Classes of Functions Related to VC Properties -- On Martingale Extensions of Vapnik-Chervonenkis -- Theory with Applications to Online Learning -- Measuring the Capacity of Sets of Functions in the Analysis of ERM -- Algorithmic Statistics Revisited -- Justifying Information-Geometric Causal Inference -- Interpretation of Black-Box Predictive Models -- PAC-Bayes Bounds for Supervised Classification -- Bounding Embeddings of VC Classes into Maximum Classes -- Algorithmic Statistics Revisited -- Justifying Information-Geometric Causal Inference -- Interpretation of Black-Box Predictive Models -- PAC-Bayes Bounds for Supervised Classification -- Bounding Embeddings of VC Classes into Maximum Classes -- Strongly Consistent Detection for Nonparametric Hypotheses -- On the Version Space Compression Set Size and Its Applications -- Lower Bounds for Sparse Coding -- Robust Algorithms via PAC-Bayes and Laplace Distributions -- Postscript: Tragic Death of Alexey Chervonenkis -- Credits -- Index.

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 statistics, and pattern recognition. The contributors are leading scientists in domains such as statistics, mathematics, and theoretical computer science, and the book will be of interest to researchers and graduate students in these domains.

ISBN: 9783319218526$q(electronic bk.)

Standard No.: 10.1007/978-3-319-21852-6doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

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505 0 $a Chervonenkis's Recollections -- A Paper That Created Three New Fields -- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities -- Sketched History: VC Combinatorics, 1826 up to 1975 -- Institute of Control Sciences through the Lens of VC Dimension -- VC Dimension, Fat-Shattering Dimension, Rademacher Averages, and Their Applications -- Around Kolmogorov Complexity: Basic Notions and Results -- Predictive Complexity for Games with Finite Outcome Spaces -- Making Vapnik-Chervonenkis Bounds Accurate -- Comment: Transductive PAC-Bayes Bounds Seen as a Generalization of Vapnik-Chervonenkis Bounds -- Comment: The Two Styles of VC Bounds -- Rejoinder: Making VC Bounds Accurate -- Measures of Complexity in the Theory of Machine Learning -- Classes of Functions Related to VC Properties -- On Martingale Extensions of Vapnik-Chervonenkis -- Theory with Applications to Online Learning -- Measuring the Capacity of Sets of Functions in the Analysis of ERM -- Algorithmic Statistics Revisited -- Justifying Information-Geometric Causal Inference -- Interpretation of Black-Box Predictive Models -- PAC-Bayes Bounds for Supervised Classification -- Bounding Embeddings of VC Classes into Maximum Classes -- Algorithmic Statistics Revisited -- Justifying Information-Geometric Causal Inference -- Interpretation of Black-Box Predictive Models -- PAC-Bayes Bounds for Supervised Classification -- Bounding Embeddings of VC Classes into Maximum Classes -- Strongly Consistent Detection for Nonparametric Hypotheses -- On the Version Space Compression Set Size and Its Applications -- Lower Bounds for Sparse Coding -- Robust Algorithms via PAC-Bayes and Laplace Distributions -- Postscript: Tragic Death of Alexey Chervonenkis -- Credits -- Index.
520 $a 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 statistics, and pattern recognition. The contributors are leading scientists in domains such as statistics, mathematics, and theoretical computer science, and the book will be of interest to researchers and graduate students in these domains.
650 0 $a Machine learning. $3 188639
650 0 $a Pattern recognition systems. $3 183725
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
650 2 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Probability and Statistics in Computer Science. $3 274053
650 2 4 $a Optimization. $3 274084
700 1 $a Chervonenkis, Alexey. $3 731159
700 1 $a Vovk, Vladimir. $3 253726
700 1 $a Papadopoulos, Harris. $3 493793
700 1 $a Gammerman, Alexander. $3 253724
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856 4 0 $u http://dx.doi.org/10.1007/978-3-319-21852-6
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