Machine Learning and Pattern Recognition

PUBLISHED


Viewing: 1 - 10 of 93
Published:
September 16, 2014
Author(s):
Kumar S. Ray
This is volume 1 of the two-volume set Soft Computing and Its Applications. This volume explains the primary tools of soft computing as well as provides an abundance of working examples and detailed design studies. The book starts with coverage of fuzzy sets and fuzzy logic and their various 
Published:
September 02, 2014
Author(s):
Ryszard Tadeusiewicz, Rituparna Chaki, Nabendu Chaki
The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations—making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.Exploring Neural Networks with C# 
Published:
August 29, 2014
Editor(s):
Biju Issac, Nauman Israr
In today’s age of wireless and mobile computing, network and computer security is paramount. Case Studies in Secure Computing: Achievements and Trends gathers the latest research from researchers who share their insights and best practices through illustrative case studies.This book examines the 
Published:
August 15, 2014
Author(s):
Kumar S. Ray
This two-volume set explains the primary tools of soft computing as well as provides an abundance of working examples and detailed design studies. The books start with coverage of fuzzy sets and fuzzy logic and their various approaches to fuzzy reasoning and go on to discuss several advanced 
Published:
July 25, 2014
Editor(s):
Charu C. Aggarwal
Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data 
Published:
July 25, 2014
Editor(s):
Thierry Bouwmans, Fatih Porikli, Benjamin Höferlin, Antoine Vacavant
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and 
Published:
June 20, 2014
Author(s):
Marco Scutari, Jean-Baptiste Denis
Understand the Foundations of Bayesian Networks—Core Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the 
Published:
February 18, 2014
Author(s):
Anthony Louis Almudevar
Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and 
Published:
February 04, 2014
Editor(s):
Oscar Humberto Montiel Ross, Roberto Sepulveda
This book examines the present and future of soft computer techniques. It explains how to use the latest technological tools, such as multicore processors and graphics processing units, to implement highly efficient intelligent system methods using a general purpose computer. 
Published:
December 20, 2013
Author(s):
Pierre Bessiere, Emmanuel Mazer, Juan Manuel Ahuactzin, Kamel Mekhnacha
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to 

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Data Mining "Nobel Prize" Awarded to Series Editor Vipin Kumar

The ACM SIGKDD 2012 Innovation Award, the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD), has been awarded to Prof. Vipin Kumar for his technical contributions to foundational research in data mining and its applications to mining scientific and climate data. Prof. Kumar is the editor of the Chapman & Hall/CRC Data Mining and Knowledge Discovery Series. He has pioneered research in the areas of high performance and parallel data mining. His research group has also been at the forefront in the development of data-driven discovery methods for analyzing global climate and ecosystem data.

 

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