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.