In Print: ‘Analytic Information Theory: From Compression to Learning’

Purdue faculty dedicate countless hours to exploring the frontiers of their respective fields, pushing the boundaries of knowledge and contributing to the ever-evolving landscape of academia. To celebrate our faculty’s excellence in scholarship, Purdue Today’s weekly book series will highlight faculty expertise across a diversity of subjects and disciplines. Today’s feature focuses on Wojciech Szpankowski, the Saul Rosen Distinguished Professor of Computer Science, and his new book, “Analytic Information Theory: From Compression to Learning.”

Publication title

Analytic Information Theory: From Compression to Learning 

Purdue author

Wojciech Szpankowski

Authors

Michael Drmota

Wojciech Szpankowski 

Publisher

Cambridge University Press

Publication date

August 2023

About the book (from the publisher) 

Through information theory, problems of communication and compression can be precisely modeled, formulated and analyzed, and this information can be transformed by means of algorithms. Also, learning can be viewed as compression with side information. Aimed at students and researchers, this book addresses data compression and redundancy within existing methods and central topics in theoretical data compression, demonstrating how to use tools from analytic combinatorics to discover and analyze precise behavior of source codes. It shows that to present better learnable or extractable information in its shortest description, one must understand what the information is, and then algorithmically extract it in its most compact form via an efficient compression algorithm. Part I covers fixed-to-variable codes such as Shannon and Huffman codes, variable-to-fixed codes such as Tunstall and Khodak codes, and variable-to-variable Khodak codes for known sources. Part II discusses universal source coding for memoryless, Markov and renewal sources.

About the Purdue author

Wojciech Szpankowski is the Saul Rosen Distinguished Professor of Computer Science at Purdue University and also holds a courtesy title as professor of electrical and computer engineering. He graduated from Gdansk University of Technology in Poland and later held several visiting professor and scholar positions at academic institutions in Canada, France, England and Germany.

Szpankowski has served as the director of the National Science Foundation’s Science and Technology Center for Science of Information since 2010. His research interests cover analysis of algorithms, information theory, bioinformatics, analytic combinatorics and stability problems of distributed systems.