Logo

Information Theory, Inference, and Learning Algorithms

Large book cover: Information Theory, Inference, and Learning Algorithms

Information Theory, Inference, and Learning Algorithms
by

Publisher: Cambridge University Press
ISBN/ASIN: 0521642981
ISBN-13: 9780521642989
Number of pages: 640

Description:
Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks.

Home page url

Download or read it online for free here:
Download link
(multiple formats)

Similar books

Book cover: Algorithmic Information TheoryAlgorithmic Information Theory
by - Cambridge University Press
The book presents the strongest possible version of Gödel's incompleteness theorem, using an information-theoretic approach based on the size of computer programs. The author tried to present the material in the most direct fashion possible.
(8527 views)
Book cover: The Limits of MathematicsThe Limits of Mathematics
by - Springer
The final version of a course on algorithmic information theory and the epistemology of mathematics. The book discusses the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical.
(8039 views)
Book cover: Entropy and Information TheoryEntropy and Information Theory
by - Springer
The book covers the theory of probabilistic information measures and application to coding theorems for information sources and noisy channels. This is an up-to-date treatment of traditional information theory emphasizing ergodic theory.
(12326 views)
Book cover: Information Theory, Excess Entropy and Statistical ComplexityInformation Theory, Excess Entropy and Statistical Complexity
by - College of the Atlantic
This e-book is a brief tutorial on information theory, excess entropy and statistical complexity. From the table of contents: Background in Information Theory; Entropy Density and Excess Entropy; Computational Mechanics.
(8567 views)