Aims and Scope

The interface between the computer and statistical sciences is a rapidly-developing field of research, as each discipline seeks to harness the power and resources of the other. This series aims to capture new developments and summarize what is known over the whole spectrum of computer science and statistics. It seeks to foster the integration of computer science and statistical, numerical and probabilistic methods by publishing a broad range of reference works, textbooks and handbooks.

The scope of the series is wide, including data mining, machine learning, AI, computational stats, exploratory data analysis, pattern recognition, learning theory, statistical software and graphics, graphical models, Bayesian data analysis, and internet data analysis. The titles included in the series are designed to appeal to students, researchers and professionals in computer and information science, statistics, mathematics, and engineering, as well as interdisciplinary researchers across many scientific disciplines. The inclusion of real examples and applications is highly encouraged, as is specific software.

Recently Published Titles

Click here to view all books in this series >>

Series Editors

David Blei
Departments of Statistics and Computer Science, Columbia University, New York, USA
[email protected]

David Madigan
Department of Statistics, Columbia University, New York, USA
[email protected]

Marina Meila
Department of Statistics, University of Washington, Seattle, USA
[email protected]

Fionn Murtagh
Goldsmiths University of London and University of Derby, UK
[email protected]

Want to Publish With Us?

If you are interested in proposing a book for the series, please contact one of the series editors or one of our statistics acquisitions editors.