Machine Learning and Pattern Recognition

96 Results


Subject


Status


Type

Machine Learning and Pattern Recognition

Per Page:
Sort:
Computational Trust Models and Machine Learning

Computational Trust Models and Machine Learning

Xin Liu, Anwitaman Datta, Ee-Peng Lim

October 29, 2014

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be...

Soft Computing and Its Applications: Volumes One and Two

Soft Computing and Its Applications: Volumes One and Two

Kumar S. Ray

October 28, 2014

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...

Regularization, Optimization, Kernels, and Support Vector Machines

Regularization, Optimization, Kernels, and Support Vector Machines

Johan A.K. Suykens, Marco Signoretto, Andreas Argyriou

October 23, 2014

Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and...

Machine Learning: An Algorithmic Perspective, Second Edition

Machine Learning: An Algorithmic Perspective, Second Edition

Stephen Marsland

October 08, 2014

A Proven, Hands-On Approach for Students without a Strong Statistical Foundation Since the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning...

Soft Computing and Its Applications, Volume Two: Fuzzy Reasoning and Fuzzy Control

Soft Computing and Its Applications, Volume Two: Fuzzy Reasoning and Fuzzy Control

Kumar S. Ray

October 07, 2014

This is volume 2 of the two-volume Soft Computing and Its Applications. This volume discusses several advanced features of soft computing and hybrid methodologies. This new book essentially contains the advanced features of soft computing and different hybrid methodologies for soft computing. The...

Soft Computing and Its Applications, Volume One: A Unified Engineering Concept

Soft Computing and Its Applications, Volume One: A Unified Engineering Concept

Kumar S. Ray

September 16, 2014

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...

Exploring Neural Networks with C#

Exploring Neural Networks with C#

Ryszard Tadeusiewicz, Rituparna Chaki, Nabendu Chaki

September 02, 2014

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#...

Case Studies in Secure Computing: Achievements and Trends

Case Studies in Secure Computing: Achievements and Trends

Biju Issac, Nauman Israr

August 29, 2014

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...

Data Classification: Algorithms and Applications

Data Classification: Algorithms and Applications

Charu C. Aggarwal

July 25, 2014

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...

Background Modeling and Foreground Detection for Video Surveillance

Background Modeling and Foreground Detection for Video Surveillance

Thierry Bouwmans, Fatih Porikli, Benjamin Höferlin, Antoine Vacavant

July 25, 2014

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...

Bayesian Networks: With Examples in R

Bayesian Networks: With Examples in R

Marco Scutari, Jean-Baptiste Denis

June 20, 2014

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...

Approximate Iterative Algorithms

Approximate Iterative Algorithms

Anthony Louis Almudevar

February 18, 2014

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...