Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying thei

The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures

This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradien

This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolut

Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dime