Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Property Testing
Property Testing is the study of super-fast (randomized) algorithms for approximate decision making. These algorithms are given direct access to items of a huge data set, and determine, whether this data set has some predetermined (global) property or is far from having this property. Remarkably, this approximate decision is made by accessing a small portion of the data set. This state-of-the-art survey presents a collection of extended abstracts and surveys of leading researchers in property testing and related areas; it reflects the program of a mini-workshop on property testing that took place in January 2010 at the Institute for Computer Science (ITCS), Tsinghua University, Beijing, China. The volume contains two editor's introductions, 10 survey papers and 18 extended abstracts.
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
This is the joint refereed proceedings of the 9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006 and the 10th International Workshop on Randomization and Computation, RANDOM 2006. The book presents 44 carefully reviewed and revised full papers. Among the topics covered are design and analysis of approximation algorithms, hardness of approximation problems, small spaces and data streaming algorithms, embeddings and metric space methods, and more.
Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques
This book constitutes the joint refereed proceedings of the 7th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2004 and the 8th International Workshop on Randomization and Computation, RANDOM 2004, held in Cambridge, MA, USA in August 2004. The 37 revised full papers presented were carefully reviewed and selected from 87 submissions. Among the issues addressed are design and analysis of approximation algorithms, inapproximability results, approximation classes, online problems, graph algorithms, cuts, geometric computations, network design and routing, packing and covering, scheduling, game theory, design and analysis of randomised algorithms, randomized complexity theory, pseudorandomness, derandomization, probabilistic proof systems, error-correcting codes, and other applications of approximation and randomness.
Foundations of Software Technology and Theoretical Computer Science
This book constitutes the refereed proceedings of the 15th International Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS '95, held in Bangalore, India in December 1995. The volume presents 31 full revised research papers selected from a total of 106 submissions together with full papers of four invited talks. Among the topics covered are algorithms, software technology, functional programming theory, distributed algorithms, term rewriting and constraint logic programming, complexity theory, process algebras, computational geometry, and temporal logics and verification theory.
Algorithmic Learning Theory
This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006. The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning.
Asymptotic Nonparametric Statistical Analysis of Stationary Time Series
Stationarity is a very general, qualitative assumption, that can be assessed on the basis of application specifics. It is thus a rather attractive assumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is that rates of convergence, even of frequencies to the mean, are not available under this assumption alone. Recently, it has been shown that, while some natural and simple problems, such as homogeneity, are indeed provably impossible to solve if one only assumes ...
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
This book constitutes the joint refereed proceedings of the 12th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2009, and the 13th International Workshop on Randomization and Computation, RANDOM 2009, held in Berkeley, CA, USA, in August 2009. The 25 revised full papers of the APPROX 2009 workshop and the 28 revised full papers of the RANDOM 2009 workshop included in this volume, were carefully reviewed and selected from 56 and 58 submissions, respectively. APPROX focuses on algorithmic and complexity issues surrounding the development of efficient approximate solutions to computationally difficult problems. RANDOM is concerned with applications of randomness to computational and combinatorial problems.
Theoretical Computer Science: Exploring New Frontiers of Theoretical Informatics
This book constitutes the refereed proceedings of the International Conference IFIP TCS 2000 held in Sendai, Japan in August 2000. The 32 revised full papers presented together with nine invited contributions were carefully reviewed and selected from a total of 70 submissions. The papers are organized in two tracks on algorithms, complexity, and models of computation and on logics, semantics, specification, and verification. The book is devoted to exploring new frontiers of theoretical informatics and addresses all current topics in theoretical computer science.
Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques
This book constitutes the refereed proceedings of the Third International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM'99, held jointly with the Second International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX'99, in Berkeley, California in August 1999. The volume presents 24 revised full papers selected from 44 submissions and four invited contributions. The papers present a wealth of new results and document the state-of-the-art in the areas covered by the workshop.
Randomization Methods in Algorithm Design
This volume is based on proceedings held during the DIMACS workshop on Randomization Methods in Algorithm Design in December 1997 at Princeton. The workshop was part of the DIMACS Special Year on Discrete Probability. It served as an interdisciplinary research workshop that brought together a mix of leading theorists, algorithmists and practitioners working in the theory and implementation aspects of algorithms involving randomization. Randomization has played an important role in the design of both sequential and parallel algorithms. The last decade has witnessed tremendous growth in the area of randomized algorithms. During this period, randomized algorithms went from being a tool in compu...
