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Regression and classification methods based on similarity of the input to stored examples have not been widely used in applications involving very large sets of high-dimensional data. Recent advances in computational geometry and machine learning, however, may alleviate the problems in using these methods on large data sets. This volume presents theoretical and practical discussions of nearest-neighbor (NN) methods in machine learning and examines computer vision as an application domain in which the benefit of these advanced methods is often dramatic. It brings together contributions from researchers in theory of computation, machine learning, and computer vision with the goals of bridging the gaps between disciplines and presenting state-of-the-art methods for emerging applications. The contributors focus on the importance of designing algorithms for NN search, and for the related classification, regression, and retrieval tasks, that remain efficient even as the number of points or the dimensionality of the data grows very large. The book begins with two theoretical chapters on computational geometry and then explores ways to make the NN approach practicable in machine learning applications where the dimensionality of the data and the size of the data sets make the naive methods for NN search prohibitively expensive. The final chapters describe successful applications of an NN algorithm, locality-sensitive hashing (LSH), to vision tasks.

Algorithms --- Geometry --- Machine learning --- Nearest neighbor analysis (Statistics) --- Data processing --- Nearest neighbour analysis (Statistics) --- Spatial analysis (Statistics) --- E-books --- COMPUTER SCIENCE/Machine Learning & Neural Networks

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Biomathematics. Biometry. Biostatistics --- Statistical physics --- Stochastic processes --- Modèle mathématique --- Mathematical models --- Méthode statistique --- Statistical methods --- Wiskundige natuurkunde --- Biomathematica. --- Stochastiques (Processus) --- Physique mathématique --- Biomathématiques. --- Stochastische processen. --- Analyse mathematique --- Probabilite --- Interacting systems --- Ising models --- Spin systems --- Markov processes --- Markov chain --- Nearest-neighbour --- Chaine de markov --- Nearest particle system --- Exclusion process

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Modern applications are both data and computationally intensive and require the storage and manipulation of voluminous traditional (alphanumeric) and nontraditional data sets (images, text, geometric objects, time-series). Examples of such emerging application domains are: Geographical Information Systems (GIS), Multimedia Information Systems, CAD/CAM, Time-Series Analysis, Medical Information Sstems, On-Line Analytical Processing (OLAP), and Data Mining. These applications pose diverse requirements with respect to the information and the operations that need to be supported. From the database perspective, new techniques and tools therefore need to be developed towards increased processing efficiency. This monograph explores the way spatial database management systems aim at supporting queries that involve the space characteristics of the underlying data, and discusses query processing techniques for nearest neighbor queries. It provides both basic concepts and state-of-the-art results in spatial databases and parallel processing research, and studies numerous applications of nearest neighbor queries.

Database management. --- Nearest neighbor analysis (Statistics) --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Nearest neighbour analysis (Statistics) --- Spatial analysis (Statistics) --- Information storage and retrieva. --- Multimedia systems. --- Data structures (Computer scienc. --- Computer science. --- Database Management. --- Information Storage and Retrieval. --- Multimedia Information Systems. --- Data Structures. --- Data Storage Representation. --- Information storage and retrieval. --- Data structures (Computer science) --- Informatics --- Science --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Multimedia information systems. --- Data structures (Computer science).