The Discrepancy Method

The Discrepancy Method PDF Author: Bernard Chazelle
Publisher: Cambridge University Press
ISBN: 9780521003575
Category : Computers
Languages : en
Pages : 500

Book Description
The discrepancy method is the glue that binds randomness and complexity. It is the bridge between randomized computation and discrepancy theory, the area of mathematics concerned with irregularities in distributions. The discrepancy method has played a major role in complexity theory; in particular, it has caused a mini-revolution of sorts in computational geometry. This book tells the story of the discrepancy method in a few short independent vignettes. It is a varied tale which includes such topics as communication complexity, pseudo-randomness, rapidly mixing Markov chains, points on the sphere and modular forms, derandomization, convex hulls, Voronoi diagrams, linear programming and extensions, geometric sampling, VC-dimension theory, minimum spanning trees, linear circuit complexity, and multidimensional searching. The mathematical treatment is thorough and self-contained. In particular, background material in discrepancy theory is supplied as needed. Thus the book should appeal to students and researchers in computer science, operations research, pure and applied mathematics, and engineering.

Geometric Discrepancy

Geometric Discrepancy PDF Author: Jiri Matousek
Publisher: Springer Science & Business Media
ISBN: 9783540655282
Category : Mathematics
Languages : en
Pages : 310

Book Description
What is the "most uniform" way of distributing n points in the unit square? How big is the "irregularity" necessarily present in any such distribution? This book is an accessible and lively introduction to the area of geometric discrepancy theory, with numerous exercises and illustrations. In separate, more specialized parts, it also provides a comprehensive guide to recent research.

The Simplex Method

The Simplex Method PDF Author: Karl Heinz Borgwardt
Publisher: Springer Science & Business Media
ISBN: 3642615783
Category : Mathematics
Languages : en
Pages : 279

Book Description
For more than 35 years now, George B. Dantzig's Simplex-Method has been the most efficient mathematical tool for solving linear programming problems. It is proba bly that mathematical algorithm for which the most computation time on computers is spent. This fact explains the great interest of experts and of the public to understand the method and its efficiency. But there are linear programming problems which will not be solved by a given variant of the Simplex-Method in an acceptable time. The discrepancy between this (negative) theoretical result and the good practical behaviour of the method has caused a great fascination for many years. While the "worst-case analysis" of some variants of the method shows that this is not a "good" algorithm in the usual sense of complexity theory, it seems to be useful to apply other criteria for a judgement concerning the quality of the algorithm. One of these criteria is the average computation time, which amounts to an anal ysis of the average number of elementary arithmetic computations and of the number of pivot steps. A rigid analysis of the average behaviour may be very helpful for the decision which algorithm and which variant shall be used in practical applications. The subject and purpose of this book is to explain the great efficiency in prac tice by assuming certain distributions on the "real-world" -problems. Other stochastic models are realistic as well and so this analysis should be considered as one of many possibilities.

The Probabilistic Method

The Probabilistic Method PDF Author: Noga Alon
Publisher: John Wiley & Sons
ISBN: 1119062071
Category : Mathematics
Languages : en
Pages : 396

Book Description
Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.

Numerical Methods for the Solution of Ill-Posed Problems

Numerical Methods for the Solution of Ill-Posed Problems PDF Author: A.N. Tikhonov
Publisher: Springer Science & Business Media
ISBN: 940158480X
Category : Mathematics
Languages : en
Pages : 257

Book Description
Many problems in science, technology and engineering are posed in the form of operator equations of the first kind, with the operator and RHS approximately known. But such problems often turn out to be ill-posed, having no solution, or a non-unique solution, and/or an unstable solution. Non-existence and non-uniqueness can usually be overcome by settling for `generalised' solutions, leading to the need to develop regularising algorithms. The theory of ill-posed problems has advanced greatly since A. N. Tikhonov laid its foundations, the Russian original of this book (1990) rapidly becoming a classical monograph on the topic. The present edition has been completely updated to consider linear ill-posed problems with or without a priori constraints (non-negativity, monotonicity, convexity, etc.). Besides the theoretical material, the book also contains a FORTRAN program library. Audience: Postgraduate students of physics, mathematics, chemistry, economics, engineering. Engineers and scientists interested in data processing and the theory of ill-posed problems.

Learning disabilities screening and evaluation guide for low- and middle-income countries

Learning disabilities screening and evaluation guide for low- and middle-income countries PDF Author: Anne M. Hayes
Publisher: RTI Press
ISBN:
Category : Education
Languages : en
Pages : 50

Book Description
Learning disabilities are among the most common disabilities experienced in childhood and adulthood. Although identifying learning disabilities in a school setting is a complex process, it is particularly challenging in low- and middle-income countries that lack the appropriate resources, tools, and supports. This guide provides an introduction to learning disabilities and describes the processes and practices that are necessary for the identification process. It also describes a phased approach that countries can use to assess their current screening and evaluation services, as well as determine the steps needed to develop, strengthen, and build systems that support students with learning disabilities. This guide also provides intervention recommendations that teachers and school administrators can implement at each phase of system development. Although this guide primarily addresses learning disabilities, the practices, processes, and systems described may be also used to improve the identification of other disabilities commonly encountered in schools.

Handbook of Response to Intervention

Handbook of Response to Intervention PDF Author: Shane R. Jimerson
Publisher: Springer Science & Business Media
ISBN: 0387490531
Category : Psychology
Languages : en
Pages : 467

Book Description
Until now, practitioners have had access to few detailed descriptions of RTI methods and the effective role they can play in special education. The Handbook of Response to Intervention fills this critical information gap. In this comprehensive volume, more than 90 expert scholars and practitioners provide a guide to the essentials of RTI assessment and identification as well as research-based interventions for improving students’ reading, writing, oral, and math skills.

Nonparametric Statistics

Nonparametric Statistics PDF Author: Ricardo Cao
Publisher: Springer
ISBN: 3319415824
Category : Mathematics
Languages : en
Pages : 231

Book Description
This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers from around the globe, and contribute to the further development of the field.

 PDF Author:
Publisher: Cambridge University Press
ISBN: 1316583988
Category :
Languages : en
Pages : 496

Book Description


Nonparametric Analysis of Univariate Heavy-Tailed Data

Nonparametric Analysis of Univariate Heavy-Tailed Data PDF Author: Natalia Markovich
Publisher: John Wiley & Sons
ISBN: 9780470723593
Category : Mathematics
Languages : en
Pages : 336

Book Description
Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution. The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function. Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.