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| Author | : Paolo Gibilisco |
| Publisher | : Cambridge University Press |
| Total Pages | : 447 |
| Release | : 2010 |
| Genre | : Mathematics |
| ISBN | : 0521896193 |
An up-to-date account of algebraic statistics and information geometry, which also explores the emerging connections between these two disciplines.
| Author | : Fedor Bogomolov |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 365 |
| Release | : 2006-06-22 |
| Genre | : Mathematics |
| ISBN | : 0817644172 |
* Contains a selection of articles exploring geometric approaches to problems in algebra, algebraic geometry and number theory * The collection gives a representative sample of problems and most recent results in algebraic and arithmetic geometry * Text can serve as an intense introduction for graduate students and those wishing to pursue research in algebraic and arithmetic geometry
| Author | : Heather A. Harrington |
| Publisher | : American Mathematical Soc. |
| Total Pages | : 277 |
| Release | : 2017-03-16 |
| Genre | : Commutative algebra -- Computational aspects and applications -- Applications of commutative algebra (e.g., to statistics, control theory, optimization, etc.) |
| ISBN | : 1470423219 |
This volume contains the proceedings of the AMS Special Session on Algebraic and Geometric Methods in Applied Discrete Mathematics, held on January 11, 2015, in San Antonio, Texas. The papers present connections between techniques from “pure” mathematics and various applications amenable to the analysis of discrete models, encompassing applications of combinatorics, topology, algebra, geometry, optimization, and representation theory. Papers not only present novel results, but also survey the current state of knowledge of important topics in applied discrete mathematics. Particular highlights include: a new computational framework, based on geometric combinatorics, for structure prediction from RNA sequences; a new method for approximating the optimal solution of a sum of squares problem; a survey of recent Helly-type geometric theorems; applications of representation theory to voting theory and game theory; a study of fixed points of tensors; and exponential random graph models from the perspective of algebraic statistics with applications to networks. This volume was written for those trained in areas such as algebra, topology, geometry, and combinatorics who are interested in tackling problems in fields such as biology, the social sciences, data analysis, and optimization. It may be useful not only for experts, but also for students who wish to gain an applied or interdisciplinary perspective.
| Author | : Michael Joswig |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 251 |
| Release | : 2013-01-04 |
| Genre | : Mathematics |
| ISBN | : 1447148177 |
Polyhedral and Algebraic Methods in Computational Geometry provides a thorough introduction into algorithmic geometry and its applications. It presents its primary topics from the viewpoints of discrete, convex and elementary algebraic geometry. The first part of the book studies classical problems and techniques that refer to polyhedral structures. The authors include a study on algorithms for computing convex hulls as well as the construction of Voronoi diagrams and Delone triangulations. The second part of the book develops the primary concepts of (non-linear) computational algebraic geometry. Here, the book looks at Gröbner bases and solving systems of polynomial equations. The theory is illustrated by applications in computer graphics, curve reconstruction and robotics. Throughout the book, interconnections between computational geometry and other disciplines (such as algebraic geometry, optimization and numerical mathematics) are established. Polyhedral and Algebraic Methods in Computational Geometry is directed towards advanced undergraduates in mathematics and computer science, as well as towards engineering students who are interested in the applications of computational geometry.
| Author | : Cristiano Bocci |
| Publisher | : Springer Nature |
| Total Pages | : 235 |
| Release | : 2019-09-11 |
| Genre | : Mathematics |
| ISBN | : 3030246248 |
This book provides an introduction to various aspects of Algebraic Statistics with the principal aim of supporting Master’s and PhD students who wish to explore the algebraic point of view regarding recent developments in Statistics. The focus is on the background needed to explore the connections among discrete random variables. The main objects that encode these relations are multilinear matrices, i.e., tensors. The book aims to settle the basis of the correspondence between properties of tensors and their translation in Algebraic Geometry. It is divided into three parts, on Algebraic Statistics, Multilinear Algebra, and Algebraic Geometry. The primary purpose is to describe a bridge between the three theories, so that results and problems in one theory find a natural translation to the others. This task requires, from the statistical point of view, a rather unusual, but algebraically natural, presentation of random variables and their main classical features. The third part of the book can be considered as a short, almost self-contained, introduction to the basic concepts of algebraic varieties, which are part of the fundamental background for all who work in Algebraic Statistics.
| Author | : David J. Saville |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 292 |
| Release | : 1996-06-20 |
| Genre | : Mathematics |
| ISBN | : 9780387947051 |
"[Suitable for] general interest readers as well as university students in their first or second year ... linear or vector geometry students who desire the illumination provided by a concrete application of the theory"--Page [1].
| Author | : Sumio Watanabe |
| Publisher | : Cambridge University Press |
| Total Pages | : 295 |
| Release | : 2009-08-13 |
| Genre | : Computers |
| ISBN | : 0521864674 |
Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
| Author | : Peter Falb |
| Publisher | : Springer |
| Total Pages | : 202 |
| Release | : 2018-08-25 |
| Genre | : Mathematics |
| ISBN | : 3319980262 |
"An introduction to the ideas of algebraic geometry in the motivated context of system theory." Thus the author describes his textbook that has been specifically written to serve the needs of students of systems and control. Without sacrificing mathematical care, the author makes the basic ideas of algebraic geometry accessible to engineers and applied scientists. The emphasis is on constructive methods and clarity rather than abstraction. The student will find here a clear presentation with an applied flavor, of the core ideas in the algebra-geometric treatment of scalar linear system theory. The author introduces the four representations of a scalar linear system and establishes the major results of a similar theory for multivariable systems appearing in a succeeding volume (Part II: Multivariable Linear Systems and Projective Algebraic Geometry). Prerequisites are the basics of linear algebra, some simple notions from topology and the elementary properties of groups, rings, and fields, and a basic course in linear systems. Exercises are an integral part of the treatment and are used where relevant in the main body of the text. The present, softcover reprint is designed to make this classic textbook available to a wider audience. "This book is a concise development of affine algebraic geometry together with very explicit links to the applications...[and] should address a wide community of readers, among pure and applied mathematicians." —Monatshefte für Mathematik
| Author | : David A. Cox |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 513 |
| Release | : 2013-04-17 |
| Genre | : Mathematics |
| ISBN | : 1475769113 |
An illustration of the many uses of algebraic geometry, highlighting the more recent applications of Groebner bases and resultants. Along the way, the authors provide an introduction to some algebraic objects and techniques more advanced than typically encountered in a first course. The book is accessible to non-specialists and to readers with a diverse range of backgrounds, assuming readers know the material covered in standard undergraduate courses, including abstract algebra. But because the text is intended for beginning graduate students, it does not require graduate algebra, and in particular, does not assume that the reader is familiar with modules.
| Author | : David J. Saville |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 567 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461209714 |
A novel exposition of the analysis of variance and regression. The key feature here is that these tools are viewed in their natural mathematical setting - the geometry of finite dimensions. This is because geometry clarifies the basic statistics and unifies the many aspects of analysing variance and regression.
