Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

Coding, information theory and compression constitute the backbone of modern digital communications and data storage. Grounded in Shannon’s seminal work, information theory quantifies the ...

Distributed source coding represents a paradigm shift in data compression, wherein multiple correlated sources are encoded independently while still enabling joint decoding. This approach contrasts ...

The IEEE European School of Information Theory (ESIT) is an annual educational event, organized by the IEEE Information Theory Society (ITSoc), for graduate students, postdocs and researchers from ...

This course gives students analytical tools to quantify information, perform inference, and study the relationship of information and learning. The course covers information measures, the source and ...

The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction.

Synthese spans the topics of Epistemology, Methodology and Philosophy of Science. Coverage includes the theory of knowledge; general methodological problems of science, of induction and probability, ...

A.I. tools from Microsoft and other companies are helping write code, placing software engineers at the forefront of the technology’s potential to disrupt the work force. By Steve Lohr Steve Lohr has ...