Skip to content

Measures of Complexity

Measures of Complexity

Festschrift for Alexey Chervonenkis
MathematicsTechnology
Pages
399
Published
2015
Language
English

Synopsis

This academic work delves into the theoretical underpinnings of machine learning, pattern recognition, and computational learning. It offers a rigorous examination of complexity measures within these fields, providing essential insights for researchers and advanced students. The book explores various methods for quantifying the difficulty and efficiency of learning algorithms.

Prose complexity
10/10

Vibe

InformativeIntellectualComplex

Genres

Mathematics Technology

Authors

A
Alexander Gammerman

Alexander Gammerman is an author recognized for his contributions to complexity theory and statistical learning. His notable works include "Measures of Complexity" and "Statistical Learning and Data Sciences," which are key texts for understanding data science and its mathematical underpinnings.

H
Harris Papadopoulos

Harris Papadopoulos writes technical texts focused on machine learning and data science. His bibliography includes Artificial Intelligence Applications and Innovations and Statistical Learning and Data Sciences. He also contributed to the AIAI 2012 International Workshops collection.

V
Vladimir Vovk

Vladimir Vovk is a distinguished author specializing in statistical learning, probability, and algorithmic complexity. His notable works include Measures of Complexity, Statistical Learning and Data Sciences, and Algorithmic Learning in a Random World. Vovk also explores game theory in Game-Theoretic Foundations for Probability and Finance.