Information Theory and Statistical Learning

This book PDF is perfect for those who love Computers genre, written by Frank Emmert-Streib and published by Springer Science & Business Media which was released on 02 May 2024 with total hardcover pages 443. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Information Theory and Statistical Learning books below.

Information Theory and Statistical Learning

Author	: Frank Emmert-Streib
File Size	: 45,5 Mb
Publisher	: Springer Science & Business Media
Language	: English
Release Date	: 02 May 2024
ISBN	: 9780387848150
Pages	: 443 pages

Get Book

Information Theory and Statistical Learning by Frank Emmert-Streib Book PDF Summary

This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.

Information Theory and Statistical Learning by Frank Emmert-Streib,Matthias Dehmer

Get Book

Information Theory Inference and Learning Algorithms by David J. C. MacKay

Table of contents

Get Book

The Nature of Statistical Learning Theory by Vladimir Vapnik

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning

Get Book

Information Theoretic Learning by Jose C. Principe

This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.

Get Book

Information Theory and Statistics by Solomon Kullback

Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.

Get Book

An Elementary Introduction to Statistical Learning Theory by Sanjeev Kulkarni,Gilbert Harman

A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of

Get Book

Algebraic Geometry and Statistical Learning Theory by Sumio Watanabe

Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.

Get Book

Principles of Digital Communication by Robert G. Gallager

The renowned communications theorist Robert Gallager brings his lucid writing style to the study of the fundamental system aspects of digital communication for a one-semester course for graduate students. With the clarity and insight that have characterized his teaching and earlier textbooks, he develops a simple framework and then combines

Get Book