Connectionists: New Machine Learning and Pattern Recognition Book Series

[Cohen, Randi]

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A Call for Authors
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Introducing a New Series from Chapman & Hall/CRC Press

Machine Learning and Pattern Recognition Series

AIMS AND SCOPE:

The field of machine learning has experienced significant growth in the
past two decades as new algorithms and techniques have been developed
and new research and applications have emerged. This series reflects the
latest advances and applications in machine learning and pattern
recognition through the publication of a broad range of reference works,
textbooks, and handbooks. We are looking for single authored works and
edited collections that will:

* Present the latest research and applications in the field, including
new mathematical, statistical, and computational methods and techniques

* Provide both introductory and advanced material for students and
professionals

* Cover a broad range of topics around learning and inference

The inclusion of concrete examples, applications, and methods is highly
encouraged. The scope of the series includes, but is not limited to,
titles in the areas of machine learning, pattern recognition,
computational intelligence, robotics, computational/statistical learning
theory, natural language processing, computer vision, game AI, game
theory, neural networks, and computational neuroscience. We are also
willing to consider other relevant topics, such as machine learning
applied to bioinformatics or cognitive science, which might be proposed
by potential contributors.

Series Editors

Ralf Herbrich
Microsoft Research Ltd. 
Cambridge, UK
Ralf.Herbrich at taylorandfrancis.com

Thore Graepel
Microsoft Research Ltd.
Cambridge, UK
Thore.Graepel at taylorandfrancis.com


Proposals for this series may be submitted to the series editors or
directly to:

Randi Cohen
Computer Science Acquisitions Editor
Chapman & Hall/CRC Press
Randi.Cohen at taylorandfrancis.com
www.crcpress.com