β Scribed by Florent Krzakala, Federico Ricci-Tersenghi, Lenka Zdeborova, Riccardo Zecchina, Eric W. Tramel, Leticia F. Cugliandolo (eds.)
No coin nor oath required. For personal study only.
This text 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.
Statistical physics;Mathematical optimization;Inference;Algorithms
π SIMILAR VOLUMES
None available in plain English.
<p><P>The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the βbestβ explanation of observed data
Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and ec
This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory