Hard spheres and related objects (hard disks and mixtures of hard systems) are paradigmatic systems: indeed, they have served as a basis for the theoretical and numerical development of a number of fields, such as general liquids and fluids, amorphous solids, liquid crystals, colloids and granular matter, to name but a few. The present volume...

Google Analytics is a free tool used by millions of Web site owners across the globe to track how visitors interact with their Web sites, where they arrive from, and which visitors drive the most revenue and sales...

The main motivation to write this book came from all our problems to find suitable material for a textbook that would really help us to teach the practical aspects of data analysis together with the needed theoretical underpinnings. Many books out there tackle either one or the other of these aspects (and, especially for the latter, there are...

Modeling problems in this book are addressed mainly from the computational viewpoint. The primary concerns are how to define an objective function for the optimal solution to a image analysis or computer vision problem and how to find the optimal solution. The solution is defined in an optimization sense because the perfect solution is...

Since 2002, FoLLI has awarded an annual prize for outstanding dissertations in the fields of Logic, Language and Information. This...

Written in a step-by-step format, this practical guide begins with an introduction to...

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the classification of similar objects into different groups, or more precisely, the partitioning of a data set into subsets...

The 2010 Asian Conference on Computer Vision took place in the southern hemisphere, in “The Land of the Long White Cloud” in Maori language, also known as New Zealand, in the beautiful town of Queenstown. If we try to segment the world we realize that New Zealand does not belong officially to any continent. Similarly, in computer...

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task....

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a...

Nowadays, computationalmethodologies of signal processing and imaging analysis for 2D, 3D and even 4D data are commonly used for various applications in society. For example, Computational Vision systems are progressively used for surveillance tasks, traffic analysis, recognition process, inspection purposes, human-machine interfaces, 3D...

The versatile capabilities and large set of add-on packages make R an excellent alternative to many existing and often expensive data mining tools. Exploring this area from the perspective of a practitioner, Data Mining with R: Learning with Case Studies uses practical examples to illustrate the power of R and data...