Measures of Complexity

Festschrift for Alexey Chervonenkis

Häftad, Engelska, 2016

AvVladimir Vovk,Harris Papadopoulos,Alexander Gammerman

1 399 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

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.

Produktinformation

Utgivningsdatum2016-10-22
Mått155 x 235 x 24 mm
Vikt651 g
FormatHäftad
SpråkEngelska
Antal sidor399
FörlagSpringer International Publishing AG
ISBN9783319357782

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Optimering inom Naturvetenskap och teknik

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.

Du kanske också är intresserad av

Del 9047

Statistical Learning and Data Sciences

Alexander Gammerman, Vladimir Vovk, Harris Papadopoulos

Häftad

729 kr

Algorithmic Learning in a Random World

Vladimir Vovk, Alexander Gammerman, Glenn Shafer

Häftad

2 359 kr

Del 9653

Conformal and Probabilistic Prediction with Applications

Alexander Gammerman, Zhiyuan Luo, Jesús Vega, Vladimir Vovk, Jesus Vega

Häftad

729 kr