Measures of Complexity

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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, optimization, computational complexity, communication complexity, inference, classification, algorithmic statistics, and pattern recognition. The contributions are leading scientists in domains such as statistics, theoretical computer science, and mathematics, and the book will be of interest to researchers and graduate students in these domains.

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