Monomial Ideals, Computations and Applications
Monomial Ideals, Computations and Applications

Author: Anna M. Bigatti

Publisher: Springer

Published: 2013-08-24

Total Pages: 201

ISBN-13: 364238742X

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This work covers three important aspects of monomials ideals in the three chapters "Stanley decompositions" by Jürgen Herzog, "Edge ideals" by Adam Van Tuyl and "Local cohomology" by Josep Álvarez Montaner. The chapters, written by top experts, include computer tutorials that emphasize the computational aspects of the respective areas. Monomial ideals and algebras are, in a sense, among the simplest structures in commutative algebra and the main objects of combinatorial commutative algebra. Also, they are of major importance for at least three reasons. Firstly, Gröbner basis theory allows us to treat certain problems on general polynomial ideals by means of monomial ideals. Secondly, the combinatorial structure of monomial ideals connects them to other combinatorial structures and allows us to solve problems on both sides of this correspondence using the techniques of each of the respective areas. And thirdly, the combinatorial nature of monomial ideals also makes them particularly well suited to the development of algorithms to work with them and then generate algorithms for more general structures.

Computational Economics and Finance
Computational Economics and Finance

Author: Hal R. Varian

Publisher: Springer Science & Business Media

Published: 1996-08-09

Total Pages: 486

ISBN-13: 9780387945187

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This collection of articles is edited by Hal Varian, Dean of the School of Information Management and Systems, University of California, Berkeley. It provides a high quality and practical selection of contributed articles that impart the expertise of an international contingent of Mathematica users from the economic, financial, investments, quantitative business and operations research communities.

Computational Network Analysis with R
Computational Network Analysis with R

Author: Matthias Dehmer

Publisher: John Wiley & Sons

Published: 2016-08-09

Total Pages: 368

ISBN-13: 3527694374

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This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.

Electronic Effects in Organic Chemistry
Electronic Effects in Organic Chemistry

Author: Barbara Kirchner

Publisher: Springer

Published: 2014-10-27

Total Pages: 197

ISBN-13: 3662435829

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The series Topics in Current Chemistry presents critical reviews of the present and future trends in modern chemical research. The scope of coverage is all areas of chemical science including the interfaces with related disciplines such as biology, medicine and materials science. The goal of each thematic volume is to give the non-specialist reader, whether in academia or industry, a comprehensive insight into an area where new research is emerging which is of interest to a larger scientific audience. Each review within the volume critically surveys one aspect of that topic and places it within the context of the volume as a whole. The most significant developments of the last 5 to 10 years are presented using selected examples to illustrate the principles discussed. The coverage is not intended to be an exhaustive summary of the field or include large quantities of data, but should rather be conceptual, concentrating on the methodological thinking that will allow the non-specialist reader to understand the information presented. Contributions also offer an outlook on potential future developments in the field. Review articles for the individual volumes are invited by the volume editors. Readership: research chemists at universities or in industry, graduate students

Text, Speech and Dialogue
Text, Speech and Dialogue

Author: Petr Sojka

Publisher: Springer

Published: 2014-09-01

Total Pages: 623

ISBN-13: 3319108166

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This book constitutes the refereed proceedings of the 17th International Conference on Text, Speech and Dialogue, TSD 2013, held in Brno, Czech Republic, in September 2014. The 70 papers presented together with 3 invited papers were carefully reviewed and selected from 143 submissions. They focus on topics such as corpora and language resources; speech recognition; tagging, classification and parsing of text and speech; speech and spoken language generation; semantic processing of text and speech; integrating applications of text and speech processing; automatic dialogue systems; as well as multimodal techniques and modelling.

An Introduction to Statistical Learning
An Introduction to Statistical Learning

Author: Gareth James

Publisher: Springer Science & Business Media

Published: 2013-06-24

Total Pages: 434

ISBN-13: 1461471389

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Fundamentals of Computational Neuroscience
Fundamentals of Computational Neuroscience

Author: Thomas Trappenberg

Publisher: Oxford University Press

Published: 2023-03-08

Total Pages: 411

ISBN-13: 0192869361

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Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the complexity of the field, and its increasing importance in progressing our understanding of how the brain works, there has long been a need for an introductory text on what is often assumed to be an impenetrable topic. The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the previous editions. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental network architectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can be gained with such studies. Each chapter starts by introducing its topic with experimental facts and conceptual questions related to the study of brain function. An additional feature is the inclusion of simple Matlab programs that can be used to explore many of the mechanisms explained in the book. An accompanying webpage includes programs for download. The book will be the essential text for anyone in the brain sciences who wants to get to grips with this topic.

Matters Computational
Matters Computational

Author: Jörg Arndt

Publisher: Springer Science & Business Media

Published: 2010-10-01

Total Pages: 980

ISBN-13: 364214764X

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This book provides algorithms and ideas for computationalists. Subjects treated include low-level algorithms, bit wizardry, combinatorial generation, fast transforms like the Fourier transform, and fast arithmetic for both real numbers and finite fields. Various optimization techniques are described and the actual performance of many given implementations is examined. The focus is on material that does not usually appear in textbooks on algorithms. The implementations are done in C++ and the GP language, written for POSIX-compliant platforms such as the Linux and BSD operating systems.

Validating Neuro-Computational Models of Neurological and Psychiatric Disorders
Validating Neuro-Computational Models of Neurological and Psychiatric Disorders

Author: Basabdatta Sen Bhattacharya

Publisher: Springer

Published: 2015-10-30

Total Pages: 329

ISBN-13: 3319200372

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This book is a collection of articles by leading researchers working at the cutting edge of neuro-computational modelling of neurological and psychiatric disorders. Each article contains model validation techniques used in the context of the specific problem being studied. Validation is essential for neuro-inspired computational models to become useful tools in the understanding and treatment of disease conditions. Currently, the immense diversity in neuro-computational modelling approaches for investigating brain diseases has created the need for a structured and coordinated approach to benchmark and standardise validation methods and techniques in this field of research. This book serves as a step towards a systematic approach to validation of neuro-computational models used for studying brain diseases and should be useful for all neuro-computational modellers.