Optimization for Data Analysis

ISBN-13: 9781316518984 / Angielski / Twarda / 2022 / 300 str.

Berkeley) Recht Benjamin (University of California

Opis

A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.

Recenzje

'This textbook is a much-needed exposition of optimization techniques, presented with conciseness and precision, with emphasis on topics most relevant for data science and machine learning applications. I imagine that this book will be immensely popular in university courses across the globe, and become a standard reference used by researchers in the area.' Amitabh Basu, Johns Hopkins University

Spis treści

1. Introduction; 2. Foundations of smooth optimization; 3. Descent methods; 4. Gradient methods using momentum; 5. Stochastic gradient; 6. Coordinate descent; 7. First-order methods for constrained optimization; 8. Nonsmooth functions and subgradients; 9. Nonsmooth optimization methods; 10. Duality and algorithms; 11. Differentiation and adjoints.