Statistical Physics, Optimization, Inference, and Message-Passing Algorithms

Krzakala, Florent|Ricci-Tersenghi, Federico|Zdeborova, Lenka|Zecchina, Riccardo|Tramel, Eric W.|Cugliandolo, Leticia F.

ISBN 10: 0198743734 / ISBN 13: 9780198743736

Published by Oxford University Press, 2016

About this Item

The book gathers the lecture notes of the Les Houches Summer School that was held in October 2013 for an audience of advanced graduate students and post-doctoral fellows in statistical physics, theoretical physics, machine learning and computer science. Seller Inventory # 151154370

Bibliographic Details

Title: Statistical Physics, Optimization, Inference...

Publisher: Oxford University Press

Publication Date: 2016

Binding: Gebunden

Condition: New

About this title

Synopsis:

In the last decade, there have been an increasing convergence of interest and methods between theoretical physics and fields as diverse as probability, machine learning, optimization and compressed sensing. In particular, many theoretical and applied works in statistical physics and computer science have relied on the use of message passing algorithms and their connection to statistical physics of spin glasses. The aim of this book, especially adapted to PhD students, post-docs, and young researchers, is to present the background necessary for entering this fast developing field.

About the Author:

Florent Krzakala is a Professor in physics at Université Pierre et Marie in Paris, France, and is doing his research in Ecole Normale Supérieure on statistical physics and disordered systems. Currently, he is leading a research team working on the development of interdisciplinary methods between statistical physics and computer science. Federico Ricci-Tersenghi is Associate Professor at the University of Rome La Sapienza, Italy. He his the co-author of "Scientific Programming: C-Language, Algorithms and Models in Science". He has an interest in the statistical physics of disordered systems, such as spin glasses, glasses, networks, optimization problems, inference and learning. Eric W. Tramel is a postdoctoral research fellow at Ecole Normale Supérieure in Paris, France, researching the interface between statistical physics and signal processing from the perspective of electrical computer engineering. Riccardo Zecchina is a professor at the Politecnico di Torino, Italy. His research interest lies at the interface between statistical physics, computer science, information theory and computational biology. Curently, he us engaged in applying the statistical physics techniques to inverse problems that arise in computational biology and neuroscience. Lenka Zdeborová is a researcher in the Institute for Theoretical Physics (IPhT) of the Centre National de la Recherche Scientifique in Saclay, France. Her main research interest are applications of methods from statistical mechanics and theoretical physics to problems in computer science, information theory, signal processing and machine learning. She was recently awarded the CNRS bronze medal for her work on statistical physics and computer science.; Leticia F. Cugliandolo is Professor at the Laboratoire de Physique Theorique et Hautes Energies Universite Pierre et Marie Curie, Paris, France. She is the director of the Les Houches School of Physics.