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Markov Random Fields for Vision and Image Processing (MIT Press)
Markov Random Fields for Vision and Image Processing (MIT Press)

This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image...

Introduction to the Theory of Programming Languages (Undergraduate Topics in Computer Science)
Introduction to the Theory of Programming Languages (Undergraduate Topics in Computer Science)
The ultimate, definitive programming language has not been created yet, far from it. Almost every day a new language is created, and new functionalities are added to existing languages. Improvements in programming languages contribute to making programs more reliable, shorten the development time, and make programs easier to...
The Theory of Gambling and Statistical Logic, Second Edition
The Theory of Gambling and Statistical Logic, Second Edition

Early in his rise to enlightenment, man invented a concept that has since been variously viewed as a vice, a crime, a business, a pleasure, a type of magic, a disease, a folly, a weakness, a form of sexual substitution, an expression of the human instinct. He invented gambling.

Recent advances in the field, particularly...

Programming Language Pragmatics, Second Edition
Programming Language Pragmatics, Second Edition
"Michael Scott's book could have been entitled: Why Programming Languages Work. It takes a fresh look at programming languages by bringing together ideas and techniques usually covered in disparate language design, compiler, computer architecture, and operating system courses. Its comprehensive and integrated presentation of language...
Building Probabilistic Graphical Models with Python
Building Probabilistic Graphical Models with Python

Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications

About This Book

  • Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image...
Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference star ting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian meth ods in applied...
Modern Statistical Methods for Astronomy: With R Applications
Modern Statistical Methods for Astronomy: With R Applications

Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to...

Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source...
Statistical Bioinformatics: with R
Statistical Bioinformatics: with R

Bioinformatics is an emerging field in which statistical and computational techniques are used extensively to analyze and interpret biological data obtained from high-throughput genomic technologies. Genomic technologies allow us to monitor thousands of biological processes going on inside living organisms in one snapshot, and are...

Artificial Organic Networks: Artificial Intelligence Based on Carbon Networks
Artificial Organic Networks: Artificial Intelligence Based on Carbon Networks

This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and...

Algorithms and Protocols for Wireless, Mobile Ad Hoc Networks (Wiley Series on Parallel and Distributed Computing)
Algorithms and Protocols for Wireless, Mobile Ad Hoc Networks (Wiley Series on Parallel and Distributed Computing)
Learn the fundamental algorithms and protocols for wireless and mobile ad hoc networks

Advances in wireless networking and mobile communication technologies, coupled with the proliferation of portable computers, have led to development efforts for wireless and mobile ad hoc networks. This book focuses on several aspects of wireless ad hoc...

Enhanced Bayesian Network Models for Spatial Time Series Prediction: Recent Research Trend in Data-Driven Predictive Analytics (Studies in Computational Intelligence)
Enhanced Bayesian Network Models for Spatial Time Series Prediction: Recent Research Trend in Data-Driven Predictive Analytics (Studies in Computational Intelligence)
This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The overall text contains many interesting results that are worth applying in practice, while it is also a source of intriguing and motivating questions for advanced research on spatial data science. 

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