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Combinatorial Geometry
A complete, self-contained introduction to a powerful and resurgingmathematical discipline . Combinatorial Geometry presents andexplains with complete proofs some of the most important resultsand methods of this relatively young mathematical discipline,started by Minkowski, Fejes Toth, Rogers, and Erd???s. Nearly halfthe results presented in this book were discovered over the pasttwenty years, and most have never before appeared in any monograph.Combinatorial Geometry will be of particular interest tomathematicians, computer scientists, physicists, and materialsscientists interested in computational geometry, robotics, sceneanalysis, and computer-aided design. It is also a superb textbook,complete with end-of-chapter problems and hints to their solutionsthat help students clarify their understanding and test theirmastery of the material. Topics covered include: * Geometric number theory * Packing and covering with congruent convex disks * Extremal graph and hypergraph theory * Distribution of distances among finitely many points * Epsilon-nets and Vapnik--Chervonenkis dimension * Geometric graph theory * Geometric discrepancy theory * And much more
Machine Learning and Knowledge Discovery in Databases
This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionalit...
COLT Proceedings 1990
COLT '90 covers the proceedings of the Third Annual Workshop on Computational Learning Theory, sponsored by the ACM SIGACT/SIGART, University of Rochester, Rochester, New York on August 6-8, 1990. The book focuses on the processes, methodologies, principles, and approaches involved in computational learning theory. The selection first elaborates on inductive inference of minimal programs, learning switch configurations, computational complexity of approximating distributions by probabilistic automata, and a learning criterion for stochastic rules. The text then takes a look at inductive identification of pattern languages with restricted substitutions, learning ring-sum-expansions, sample co...
Algorithmic Learning Theory
This book constitutes the refereed proceedings of the 16th International Conference on Algorithmic Learning Theory, ALT 2005, held in Singapore in October 2005. The 30 revised full papers presented together with 5 invited papers and an introduction by the editors were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on kernel-based learning, bayesian and statistical models, PAilearning, query-learning, inductive inference, language learning, learning and logic, learning from expert advice, online learning, defensive forecasting, and teaching.
Parallel Program Development for Cluster Computing
The book is divided into two parts, the first one covering the concepts and methodologies, and the second describing the tools and integrated environments that were developed in those projects. In this way, we hope that the reader will find the book useful not only concerning an identification of current trends in parallel program development, but also concerning their practical illustration through concrete tools and environments.
Technology Supporting Business Solutions
The explosive growth of the Internet and the web have created an ever-growing demand for web-based information systems, and ever-growing challenges for Information Systems Engineering. Some of them include the emerging web services technology, database technologies and application integration, as well as data analysis and knowledge discovery. This book is a showcase of recent, significant advances in web-based information systems as well as data integration and analysis. It provides an overview of various technologies used for building innovative information systems applied to real business solutions. It includes eight chapters that are divided into five parts, namely: web services, database technologies, data and application integration, data analysis and knowledge discovery, and recommended bibliography. The material presented in these chapters will help the reader have an overall idea of the research that is being carried out in universities and companies to develop today's innovative business solutions. Contents: Preface; Web Services; Web Services Technologies for Outsourcing; Conceptual Modelling with Dynamic Object Roles; Temporal Versioning in Data Warehouse; Missing Inform
STACS 2003
This book constitutes the refereed proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science, STACS 2003, held in Berlin, Germany in February/March 2003. The 58 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 253 submissions. The papers address the whole range of theoretical computer science including algorithms and data structures, automata and formal languages, complexity theory, semantics, logic in computer science, as well as current challenges like biological computing, quantum computing, and mobile and net computing.
Automata, Languages and Programming
The two-volume set LNCS 4051 and LNCS 4052 constitutes the refereed proceedings of the 33rd International Colloquium on Automata, Languages and Programming, ICALP 2006, held in Venice, Italy, July 2006. In all, these volumes present more 100 papers and lectures. Volume I (4051) presents 61 revised full papers together with 1 invited lecture, focusing on algorithms, automata, complexity and games, on topics including graph theory, quantum computing, and more.
Learning Theory and Kernel Machines
This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.
Machines that Learn to Play Games
The mind-set that has dominated the history of computer game playing relies on straightforward exploitation of the available computing power. The fact that a machine can explore millions of variations sooner than the sluggish human can wink an eye has inspired hopes that the mystery of intelligence can be cracked, or at least side-stepped, by sheer force. Decades of the steadily growing strength of computer programs have attested to the soundness of this approach. It is clear that deeper understanding can cut the amount of necessary calculations by orders of magnitude. The papers collected in this volume describe how to instill learning skills in game playing machines. The reader is asked to keep in mind that this is not just about games -- the possibility that the discussed techniques will be used in control systems and in decision support always looms in the background.
