Linear Algebraic Techniques in Algorithms and Complexity PDF Download

Author: Joshua H. Alman
Publisher:
ISBN:
Category :
Languages : en
Pages : 224

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Book Description
We develop linear algebraic techniques in algorithms and complexity, and apply them to a variety of different problems. We focus in particular on matrix multiplication algorithms, which have surprisingly fast running times and can hence be used to design fast algorithms in many settings, and matrix rank methods, which can be used to design algorithms or prove lower bounds by analyzing the ranks of matrices corresponding to computational tasks. First, we study the design of matrix multiplication algorithms. We define a new general method, called the Universal Method, which subsumes all the known approaches to designing these algorithms. We then design a suite of techniques for proving lower bounds on the running times which can be achieved by algorithms using many tensors and the Universal Method. Our main limitation result is that a large class of tensors generalizing the Coppersmith-Winograd tensors (the family of tensors used in all record-holding algorithms for the past 30+ years) cannot achieve a better running time for multiplying n by n matrices than O(n2[superscript .]168). Second, we design faster algorithms for batch nearest neighbor search, the problem where one is given sets of data points and query points, and one wants to find the most similar data point to each query point, according to some distance measure. We give the first subquadratic time algorithm for the exact problem in high dimensions, and the fastest known algorithm for the approximate problem, for various distance measures including Hamming and Euclidean distance. Our algorithms make use of new probabilistic polynomial constructions to reduce the problem to the multiplication of low-rank matrices. Third, we study rigid matrices, which cannot be written as the sum of a low rank matrix and a sparse matrix. Finding explicit rigid matrices is an important open problem in complexity theory with applications in many different areas. We show that the Walsh-Hadamard transform, previously a leading candidate rigid matrix, is in fact not rigid. We also give the first nontrivial construction of rigid matrices in a certain parameter regime with applications to communication complexity, using an efficient algorithm with access to an NP oracle.

Author: Satyanarayana V. Lokam
Publisher: Now Publishers Inc
ISBN: 1601982429
Category : Computers
Languages : en
Pages : 177

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Book Description
We survey several techniques for proving lower bounds in Boolean, algebraic, and communication complexity based on certain linear algebraic approaches. The common theme among these approaches is to study robustness measures of matrix rank that capture the complexity in a given model. Suitably strong lower bounds on such robustness functions of explicit matrices lead to important consequences in the corresponding circuit or communication models. Many of the linear algebraic problems arising from these approaches are independently interesting mathematical challenges.

Author: Jeremy Kepner
Publisher: SIAM
ISBN: 9780898719918
Category : Mathematics
Languages : en
Pages : 388

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Book Description
The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance.

Author: Dario Bini
Publisher: Springer Science & Business Media
ISBN: 1461202655
Category : Computers
Languages : en
Pages : 433

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Book Description
Our Subjects and Objectives. This book is about algebraic and symbolic computation and numerical computing (with matrices and polynomials). It greatly extends the study of these topics presented in the celebrated books of the seventies, [AHU] and [BM] (these topics have been under-represented in [CLR], which is a highly successful extension and updating of [AHU] otherwise). Compared to [AHU] and [BM] our volume adds extensive material on parallel com putations with general matrices and polynomials, on the bit-complexity of arithmetic computations (including some recent techniques of data compres sion and the study of numerical approximation properties of polynomial and matrix algorithms), and on computations with Toeplitz matrices and other dense structured matrices. The latter subject should attract people working in numerous areas of application (in particular, coding, signal processing, control, algebraic computing and partial differential equations). The au thors' teaching experience at the Graduate Center of the City University of New York and at the University of Pisa suggests that the book may serve as a text for advanced graduate students in mathematics and computer science who have some knowledge of algorithm design and wish to enter the exciting area of algebraic and numerical computing. The potential readership may also include algorithm and software designers and researchers specializing in the design and analysis of algorithms, computational complexity, alge braic and symbolic computing, and numerical computation.

Author: Vadim Olshevsky
Publisher: World Scientific
ISBN: 9812836020
Category : Mathematics
Languages : en
Pages : 604

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Book Description
Operators preserving primitivity for matrix pairs / L.B. Beasley, A.E. Guterman -- Decompositions of quaternions and their matrix equivalents / D. Janovská, G. Opfer -- Sensitivity analysis of Hamiltonian and reversible systems prone to dissipation-induced instabilities / O.N. Kirillov -- Block triangular miniversal deformations of matrices and matrix pencils / L. Klimenko, V.V. Sergeichuk -- Determining the Schein rank of boolean matrices / E.E. Marenich -- Lattices of matrix rows and matrix columns. Lattices of invariant column eigenvectors / V. Marenich -- Matrix algebras and their length / O.V. Markova -- On a new class of singular nonsymmetric matrices with nonnegative integer spectra / T. Nahtman, D. von Rosen -- Reduction of a set of matrices over a principal ideal domain to the Smith normal forms by means of the same one-sided transformation / V.M. Prokip -- Nonsymmetric algebraic Riccati equations associated with an M-matrix : recent advances and algorithms / D.A. Bini, B. Iannazzo, B. Meini, F. Poloni -- A generalized conjugate direction method for nonsymmetric large ill-conditioned linear systems / E.R. Boudinov, A.I. Manevich -- There exist normal Hankel ([symbol], [symbol])-circulants of any order [symbol] / V.N. Chugunov, Kh. D. Ikramov -- On the treatment of boundary artifacts in image restoration by reflection and/or anti-reflection / M. Donatelli, S. Serra-Capizzano -- Zeros of determinants of [symbol]-matrices / W. Gander -- How to find a good submatrix / S.A. Goreinov [und weiteren] -- Conjugate and semi-conjugate direction methods with preconditioning projectors / V.P. Il'in -- Some relationships between optimal preconditioner and superoptimal preconditioner / J.-B. Chen [und weiteren] -- Scaling, preconditioning, and superlinear convergence in GMRES-type iterations / I. Kaporin -- Toeplitz and Toeplitz-block-Toeplitz matrices and their correlation with syzygies of polynomials / H. Khalil, B. Mourrain, M. Schatzman -- Concepts of data-sparse tensor-product approximation in many-particle modelling / H.-J. Flad [und weiteren] -- Separation of variables in nonlinear fermi equation / Yu. I. Kuznetsov -- Faster multipoint polynomial evaluation via structured matrices / B. Murphy, R.E. Rosholt -- Testing pivoting policies in Gaussian elimination / B. Murphy [und weiteren] -- Newton's iteration for matrix inversion, advances and extensions / V.Y. Pan -- Truncated decompositions and filtering methods with reflective/antireflective boundary conditions : a comparison / C. Tablino Possio -- Discrete-time stability of a class of hermitian polynomial matrices with positive semidefinite coefficients / H.K. Wimmer -- Splitting algorithm for solving mixed variational inequalities with inversely strongly monotone operators / I. Badriev, O. Zadvornov -- Multilevel algorithm for graph partitioning / N.S. Bochkarev, O.V. Diyankov, V.Y. Pravilnikov -- 2D-extension of singular spectrum analysis : algorithm and elements of theory / N.E. Golyandina, K.D. Usevich -- Application of radon transform for fast solution of boundary value problems for elliptic PDE in domains with complicated geometry / A.I. Grebennikov -- Application of a multigrid method to solving diffusion-type equations / M.E. Ladonkina, O. Yu. Milukova, V.F. Tishkin -- Monotone matrices and finite volume schemes for diffusion problems preserving non-negativity of solution / I.V. Kapyrin -- Sparse approximation of FEM matrix for sheet current integro-differential equation / M. Khapaev, M. Yu. Kupriyanov -- The method of magnetic field computation in presence of an ideal conductive multiconnected surface by using the integro-differential equation of the first kind / T. Kochubey, V.I. Astakhov -- Spectral model order reduction preserving passivity for large multiport RCLM networks / Yu. M. Nechepurenko, A.S. Potyagalova, I.A. Karaseva -- New smoothers in multigrid methods for strongly nonsymmetric linear systems / G.V. Muratova, E.M. Andreeva -- Operator equations for eddy currents on singular carriers / J. Naumenko -- Matrix approach to modelling of polarized radiation transfer in heterogeneous systems / T.A. Sushkevich, S.A. Strelkov, S.V. Maksakova -- The Method of Regularization of Tikhonov Based on Augmented Systems / A.I. Zhdanov, T.G. Parchaikina

Author: Tom Lyche
Publisher: Springer Nature
ISBN: 3030364682
Category : Mathematics
Languages : en
Pages : 376

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Book Description
After reading this book, students should be able to analyze computational problems in linear algebra such as linear systems, least squares- and eigenvalue problems, and to develop their own algorithms for solving them. Since these problems can be large and difficult to handle, much can be gained by understanding and taking advantage of special structures. This in turn requires a good grasp of basic numerical linear algebra and matrix factorizations. Factoring a matrix into a product of simpler matrices is a crucial tool in numerical linear algebra, because it allows us to tackle complex problems by solving a sequence of easier ones. The main characteristics of this book are as follows: It is self-contained, only assuming that readers have completed first-year calculus and an introductory course on linear algebra, and that they have some experience with solving mathematical problems on a computer. The book provides detailed proofs of virtually all results. Further, its respective parts can be used independently, making it suitable for self-study. The book consists of 15 chapters, divided into five thematically oriented parts. The chapters are designed for a one-week-per-chapter, one-semester course. To facilitate self-study, an introductory chapter includes a brief review of linear algebra.

Author: Bhubaneswar Mishra
Publisher: Springer Science & Business Media
ISBN: 1461243440
Category : Computers
Languages : en
Pages : 427

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Book Description
Algorithmic Algebra studies some of the main algorithmic tools of computer algebra, covering such topics as Gröbner bases, characteristic sets, resultants and semialgebraic sets. The main purpose of the book is to acquaint advanced undergraduate and graduate students in computer science, engineering and mathematics with the algorithmic ideas in computer algebra so that they could do research in computational algebra or understand the algorithms underlying many popular symbolic computational systems: Mathematica, Maple or Axiom, for instance. Also, researchers in robotics, solid modeling, computational geometry and automated theorem proving community may find it useful as symbolic algebraic techniques have begun to play an important role in these areas. The book, while being self-contained, is written at an advanced level and deals with the subject at an appropriate depth. The book is accessible to computer science students with no previous algebraic training. Some mathematical readers, on the other hand, may find it interesting to see how algorithmic constructions have been used to provide fresh proofs for some classical theorems. The book also contains a large number of exercises with solutions to selected exercises, thus making it ideal as a textbook or for self-study.

Author: Richard Bronson
Publisher: Elsevier/AP, Academic Press is
ISBN: 9789351071792
Category : Algebras, Linear
Languages : en
Pages : 0

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Book Description

Author: Jonathan S. Golan
Publisher: Springer Science & Business Media
ISBN: 9400726368
Category : Mathematics
Languages : en
Pages : 499

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Book Description
Linear algebra is a living, active branch of mathematics which is central to almost all other areas of mathematics, both pure and applied, as well as to computer science, to the physical, biological, and social sciences, and to engineering. It encompasses an extensive corpus of theoretical results as well as a large and rapidly-growing body of computational techniques. Unfortunately, in the past decade, the content of linear algebra courses required to complete an undergraduate degree in mathematics has been depleted to the extent that they fail to provide a sufficient theoretical or computational background. Students are not only less able to formulate or even follow mathematical proofs, they are also less able to understand the mathematics of the numerical algorithms they need for applications. Certainly, the material presented in the average undergraduate course is insufficient for graduate study. This book is intended to fill the gap which has developed by providing enough theoretical and computational material to allow the advanced undergraduate or beginning graduate student to overcome this deficiency and be able to work independently or in advanced courses. The book is intended to be used either as a self-study guide, a textbook for a course in advanced linear algebra, or as a reference book. It is also designed to prepare a student for the linear algebra portion of prelim exams or PhD qualifying exams. The volume is self-contained to the extent that it does not assume any previous formal knowledge of linear algebra, though the reader is assumed to have been exposed, at least informally, to some of the basic ideas and techniques, such as manipulation of small matrices and the solution of small systems of linear equations over the real numbers. More importantly, it assumes a seriousness of purpose, considerable motivation, and a modicum of mathematical sophistication on the part of the reader. In the latest edition, new major theorems have been added, as well as many new examples. There are over 130 additional exercises and many of the previous exercises have been revised or rewritten. In addition, a large number of additional biographical notes and thumbnail portraits of mathematicians have been included.

Author: Eric Darve
Publisher: SIAM
ISBN: 1611976553
Category : Mathematics
Languages : en
Pages : 420

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Book Description
Numerical Linear Algebra with Julia provides in-depth coverage of fundamental topics in numerical linear algebra, including how to solve dense and sparse linear systems, compute QR factorizations, compute the eigendecomposition of a matrix, and solve linear systems using iterative methods such as conjugate gradient. Julia code is provided to illustrate concepts and allow readers to explore methods on their own. Written in a friendly and approachable style, the book contains detailed descriptions of algorithms along with illustrations and graphics that emphasize core concepts and demonstrate the algorithms. Numerical Linear Algebra with Julia is a textbook for advanced undergraduate and graduate students in most STEM fields and is appropriate for courses in numerical linear algebra. It may also serve as a reference for researchers in various fields who depend on numerical solvers in linear algebra.