Perturbations, Optimization, and Statistics (Neural Information Processing series) - Softcover

Softcover

ISBN 10: 0262549948 ISBN 13: 9780262549943

Publisher: MIT Press, 2023

Synopsis

A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees.

In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a supervised learning setting. An emerging body of work on learning under different rules applies perturbations to decision and learning procedures. These methods provide simple and highly efficient learning rules with improved theoretical guarantees. This book describes perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees, offering readers a state-of-the-art overview.

Chapters address recent modeling ideas that have arisen within the perturbations framework, including Perturb & MAP, herding, and the use of neural networks to map generic noise to distribution over highly structured data. They describe new learning procedures for perturbation models, including an improved EM algorithm and a learning algorithm that aims to match moments of model samples to moments of data. They discuss understanding the relation of perturbation models to their traditional counterparts, with one chapter showing that the perturbations viewpoint can lead to new algorithms in the traditional setting. And they consider perturbation-based regularization in neural networks, offering a more complete understanding of dropout and studying perturbations in the context of deep neural networks.

About this title

About the Authors

Tamir Hazan is Assistant Professor at Technion, Israel Institute of Technology.

George Papandreou is a Research Scientist for Google, Inc.

Daniel Tarlow is a Researcher at Microsoft Research Cambridge, UK.

Edition details

• Publisher: MIT Press
• Publication date: 2023
• Language: English
• ISBN 10: 0262549948
• ISBN 13: 9780262549943
• Binding: Paperback
• Number of pages: 412
• Editor: Hazan Tamir, Papandreou George, Tarlow Daniel