Matrix Methods in Data Mining and Pattern Recognition, Lars Elden
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 66520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Автор: Matveev, Andrey O., Название: Pattern recognition on oriented matroids / ISBN: 3110530716 ISBN-13(EAN): 9783110530711 Издательство: Walter de Gruyter Рейтинг: Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Pattern Recognition on Oriented Matroids covers a range of innovative problems in combinatorics, poset and graph theories, optimization, and number theory that constitute a far-reaching extension of the arsenal of committee methods in pattern recognition. The groundwork for the modern committee theory was laid in the mid-1960s, when it was shown that the familiar notion of solution to a feasible system of linear inequalities has ingenious analogues which can serve as collective solutions to infeasible systems. A hierarchy of dialects in the language of mathematics, for instance, open cones in the context of linear inequality systems, regions of hyperplane arrangements, and maximal covectors (or topes) of oriented matroids, provides an excellent opportunity to take a fresh look at the infeasible system of homogeneous strict linear inequalities - the standard working model for the contradictory two-class pattern recognition problem in its geometric setting. The universal language of oriented matroid theory considerably simplifies a structural and enumerative analysis of applied aspects of the infeasibility phenomenon.
The present book is devoted to several selected topics in the emerging theory of pattern recognition on oriented matroids: the questions of existence and applicability of matroidal generalizations of committee decision rules and related graph-theoretic constructions to oriented matroids with very weak restrictions on their structural properties; a study (in which, in particular, interesting subsequences of the Farey sequence appear naturally) of the hierarchy of the corresponding tope committees; a description of the three-tope committees that are the most attractive approximation to the notion of solution to an infeasible system of linear constraints; an application of convexity in oriented matroids as well as blocker constructions in combinatorial optimization and in poset theory to enumerative problems on tope committees; an attempt to clarify how elementary changes (one-element reorientations) in an oriented matroid affect the family of its tope committees; a discrete Fourier analysis of the important family of critical tope committees through rank and distance relations in the tope poset and the tope graph; the characterization of a key combinatorial role played by the symmetric cycles in hypercube graphs.
Contents Oriented Matroids, the Pattern Recognition Problem, and Tope Committees Boolean Intervals Dehn-Sommerville Type Relations Farey Subsequences Blocking Sets of Set Families, and Absolute Blocking Constructions in Posets Committees of Set Families, and Relative Blocking Constructions in Posets Layers of Tope Committees Three-Tope Committees Halfspaces, Convex Sets, and Tope Committees Tope Committees and Reorientations of Oriented Matroids Topes and Critical Committees Critical Committees and Distance Signals Symmetric Cycles in the Hypercube Graphs
Автор: Pelillo Название: Energy Minimization Methods in Computer Vision and Pattern Recognition ISBN: 3319781987 ISBN-13(EAN): 9783319781983 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions.
Автор: Damir Gainanov Название: Graphs for Pattern Recognition: Infeasible Systems of Linear Inequalities ISBN: 3110480131 ISBN-13(EAN): 9783110480139 Издательство: Walter de Gruyter Рейтинг: Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition.Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms thanks to the committee method. Such infeasible systems of inequalities represent an important special subclass of infeasible systems of constraints with a monotonicity property - systems whose multi-indices of feasible subsystems form abstract simplicial complexes (independence systems), which are fundamental objects of combinatorial topology.The methods of data mining and machine learning discussed in this monograph form the foundation of technologies like big data and deep learning, which play a growing role in many areas of human-technology interaction and help to find solutions, better solutions and excellent solutions. Contents: PrefacePattern recognition, infeasible systems of linear inequalities, and graphsInfeasible monotone systems of constraintsComplexes, (hyper)graphs, and inequality systemsPolytopes, positive bases, and inequality systemsMonotone Boolean functions, complexes, graphs, and inequality systemsInequality systems, committees, (hyper)graphs, and alternative coversBibliographyList of notationIndex
Автор: Tobias Preusser, Robert M. Kirby, Torben Patz Название: Stochastic Partial Differential Equations for Computer Vision with Uncertain Data ISBN: 1681731436 ISBN-13(EAN): 9781681731438 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 56370.00 T Наличие на складе: Невозможна поставка. Описание: The goal of this book is to introduce the reader to the recent advances from the field of uncertainty quantification and error propagation for computer vision, image processing, and image analysis that are based on partial differential equations (PDEs). It presents a concept with which error propagation and sensitivity analysis can be formulated with a set of basic operations.
Автор: Martha Refugio Ortiz-Posadas Название: Pattern Recognition Techniques Applied to Biomedical Problems ISBN: 3030380203 ISBN-13(EAN): 9783030380205 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers pattern recognition techniques applied to various areas of biomedicine, including disease diagnosis and prognosis, and several problems of classification, with a special focus on-but not limited to-pattern recognition modeling of biomedical signals and images.
Автор: Niels da Vitoria Lobo; Takis Kasparis; Michael Geo Название: Structural, Syntactic, and Statistical Pattern Recognition ISBN: 3540896880 ISBN-13(EAN): 9783540896883 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Contains papers organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, and computer vision and biometrics.
Автор: Ostalczyk Piotr Название: Discrete Fractional Calculus: Applications In Control And Image Processing ISBN: 9814725668 ISBN-13(EAN): 9789814725668 Издательство: World Scientific Publishing Цена: 141510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The main subject of the monograph is the fractional calculus in the discrete version.
Автор: Erik Cuevas; Daniel Zald?var; Marco Perez-Cisneros Название: Applications of Evolutionary Computation in Image Processing and Pattern Recognition ISBN: 3319264605 ISBN-13(EAN): 9783319264608 Издательство: Springer Рейтинг: Цена: 130610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the use of efficientEvolutionary Computation (EC) algorithms for solving diverse real-world imageprocessing and pattern recognition problems.
Автор: Geoff Dougherty Название: Pattern Recognition and Classification ISBN: 1493953354 ISBN-13(EAN): 9781493953356 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume, both comprehensive and accessible, introduces all the key concepts in pattern recognition, and includes many examples and exercises that make it an ideal guide to an important methodology widely deployed in today`s ubiquitous automated systems.
Автор: Alan L. Yuille; Francisco Escolano Ruiz; Pablo Sua Название: Information Theory in Computer Vision and Pattern Recognition ISBN: 1447156935 ISBN-13(EAN): 9781447156932 Издательство: Springer Рейтинг: Цена: 93130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides comprehensive coverage of information theory elements implied in modern CVPR algorithms. It introduces information theory to researchers in CVPR, and additionally introduces interesting CVPR problems to information theorists.
Автор: Pedro Latorre Carmona; J. Salvador S?nchez; Ana L. Название: Mathematical Methodologies in Pattern Recognition and Machine Learning ISBN: 1493900927 ISBN-13(EAN): 9781493900923 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012.
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