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This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at mary.james@springer.com. This is an open access book.
Maths for computer scientists --- Communications engineering / telecommunications --- Maths for engineers --- Probability & statistics --- Probability and Statistics in Computer Science --- Communications Engineering, Networks --- Mathematical and Computational Engineering --- Probability Theory and Stochastic Processes --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences --- Mathematical and Computational Engineering Applications --- Probability Theory --- Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences --- Applied probability --- Hypothesis testing --- Detection theory --- Expectation maximization --- Stochastic dynamic programming --- Machine learning --- Stochastic gradient descent --- Deep neural networks --- Matrix completion --- Linear and polynomial regression --- Open Access --- Mathematical & statistical software --- Stochastics
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"Totally nonnegative matrices arise in a remarkable variety of mathematical applications. This book is a comprehensive and self-contained study of the essential theory of totally nonnegative matrices, defined by the nonnegativity of all subdeterminants. It explores methodological background, historical highlights of key ideas, and specialized topics.The book uses classical and ad hoc tools, but a unifying theme is the elementary bidiagonal factorization, which has emerged as the single most important tool for this particular class of matrices. Recent work has shown that bidiagonal factorizations may be viewed in a succinct combinatorial way, leading to many deep insights. Despite slow development, bidiagonal factorizations, along with determinants, now provide the dominant methodology for understanding total nonnegativity. The remainder of the book treats important topics, such as recognition of totally nonnegative or totally positive matrices, variation diminution, spectral properties, determinantal inequalities, Hadamard products, and completion problems associated with totally nonnegative or totally positive matrices. The book also contains sample applications, an up-to-date bibliography, a glossary of all symbols used, an index, and related references"-- "Totally Nonnegative Matrices" is a comprehensive, modern treatment of the titled class of matrices that arise in very many ways. Methodological background is given, and elementary bidiagonal factorization is a featured tool. In addition to historical highlights and sources of interest, some of the major topics include: recognition, variation diminution, spectral structure, determinantal inequalities, Hadamard products, and completion problems. "--
Non-negative matrices. --- Nonnegative matrices --- Matrices --- EB factorization. --- Hadamard core. --- Hadamard multiplication. --- Hadamard powers. --- Hadamard products. --- IITN matrices. --- Jacobi matrices. --- LU factorization. --- MLBC graphs. --- Perron complements. --- Perron-Frobenius theory. --- TN completions. --- TN linear transformations. --- TN matrices. --- TN matrix structure. --- TN matrix. --- TN perturbations. --- TN polynomial matrices. --- TP intervals. --- TP matrices. --- TP matrix. --- TP polynomial matrices. --- Vandermonde matrices. --- bidiagonal factorization. --- completions. --- constructions. --- core matrix theory. --- detemrinants. --- determinantal identities. --- determinantal inequalities. --- direct summation. --- eigenvalues. --- eigenvectors. --- elementary linear algebra. --- extensions. --- line insertion. --- linear transformations. --- matrix completion problems. --- matrix theory. --- nonnegativity. --- numerical analysis. --- partial TN matrices. --- planar diagrams. --- positive minors. --- positive semidefinite matrices. --- positivity. --- powers. --- principal minors. --- rank deficiency. --- rank deficient submatrices. --- recognition. --- retractions. --- roots. --- sign variation diminution. --- spectral properties. --- statistics. --- subdeterminants. --- subdirect sums. --- total positivity. --- totally nonnegative matrices. --- totally positive matrices. --- triangular factorization. --- variation diminution. --- vectors.
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