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Book Kernels for Structured Data

Download or read book Kernels for Structured Data written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Kernels for Structured Data

Download or read book Kernels for Structured Data written by Thomas Gartner and published by World Scientific. This book was released on 2008 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by their atoms and bonds. The book guides the reader from the basics of kernel methods to advanced algorithms and kernel design for structured data. It is thus useful for readers who seek an entry point into the field as well as experienced researchers.

Book Kernels for Structured Data

Download or read book Kernels for Structured Data written by Thomas G„rtner and published by World Scientific. This book was released on 2008 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by their atoms and bonds. The book guides the reader from the basics of kernel methods to advanced algorithms and kernel design for structured data. It is thus useful for readers who seek an entry point into the field as well as experienced researchers.

Book Kernel Methods in Computational Biology

Download or read book Kernel Methods in Computational Biology written by Bernhard Schölkopf and published by MIT Press. This book was released on 2004 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed overview of current research in kernel methods and their application to computational biology.

Book Kernel Methods for Pattern Analysis

Download or read book Kernel Methods for Pattern Analysis written by John Shawe-Taylor and published by Cambridge University Press. This book was released on 2004-06-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description

Book Kernel Methods for Pattern Analysis

Download or read book Kernel Methods for Pattern Analysis written by John Shawe-Taylor and published by Cambridge University Press. This book was released on 2004-06-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed from lectures and tutorials, fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to use for standard pattern discovery problems in fields such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.

Book Predicting Structured Data

    Book Details:
  • Author : Neural Information Processing Systems Foundation
  • Publisher : MIT Press
  • Release : 2007
  • ISBN : 0262026171
  • Pages : 361 pages

Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Book Inductive Logic Programming

    Book Details:
  • Author : Stan Matwin
  • Publisher : Springer Science & Business Media
  • Release : 2003-02-12
  • ISBN : 9783540005674
  • Pages : 372 pages

Download or read book Inductive Logic Programming written by Stan Matwin and published by Springer Science & Business Media. This book was released on 2003-02-12 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 12th International Conference on Inductive Logic Programming, ILP 2002, held in Sydney, Australia in July 2002. The 22 revised full papers presented were carefully selected during two rounds of reviewing and revision from 45 submissions. Among the topics addressed are first order decision lists, learning with description logics, bagging in ILP, kernel methods, concept learning, relational learners, description logic programs, Bayesian classifiers, knowledge discovery, data mining, logical sequences, theory learning, stochastic logic programs, machine discovery, and relational pattern discovery.

Book Inductive Logic Programming

Download or read book Inductive Logic Programming written by Stan Matwin and published by Springer Science & Business Media. This book was released on 2003-02-12 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 12th International Conference on Inductive Logic Programming, ILP 2002, held in Sydney, Australia in July 2002. The 22 revised full papers presented were carefully selected during two rounds of reviewing and revision from 45 submissions. Among the topics addressed are first order decision lists, learning with description logics, bagging in ILP, kernel methods, concept learning, relational learners, description logic programs, Bayesian classifiers, knowledge discovery, data mining, logical sequences, theory learning, stochastic logic programs, machine discovery, and relational pattern discovery.

Book Graph Kernels

    Book Details:
  • Author : Karsten Borgwardt
  • Publisher :
  • Release : 2020-12-22
  • ISBN : 9781680837704
  • Pages : 198 pages

Download or read book Graph Kernels written by Karsten Borgwardt and published by . This book was released on 2020-12-22 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book

    Book Details:
  • Author :
  • Publisher : IOS Press
  • Release :
  • ISBN :
  • Pages : 3525 pages

Download or read book written by and published by IOS Press. This book was released on with total page 3525 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Handbook of Computational Statistics

Download or read book Handbook of Computational Statistics written by James E. Gentle and published by Springer Science & Business Media. This book was released on 2012-07-06 with total page 1180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.

Book Machine Learning  ECML 2006

    Book Details:
  • Author : Johannes Fürnkranz
  • Publisher : Springer Science & Business Media
  • Release : 2006-09-19
  • ISBN : 354045375X
  • Pages : 873 pages

Download or read book Machine Learning ECML 2006 written by Johannes Fürnkranz and published by Springer Science & Business Media. This book was released on 2006-09-19 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held, jointly with PKDD 2006. The book presents 46 revised full papers and 36 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers present a wealth of new results in the area and address all current issues in machine learning.

Book The Christoffel   Darboux Kernel for Data Analysis

Download or read book The Christoffel Darboux Kernel for Data Analysis written by Jean Bernard Lasserre and published by Cambridge University Press. This book was released on 2022-04-07 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible overview introduces the Christoffel-Darboux kernel as a novel, simple and efficient tool in statistical data analysis.

Book Knowledge Based Intelligent Information and Engineering Systems

Download or read book Knowledge Based Intelligent Information and Engineering Systems written by Ignac Lovrek and published by Springer. This book was released on 2008-09-20 with total page 1079 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNAI 5177, LNAI 5178, and LNAI 5179, constitutes the refereed proceedings of the 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, held in Zagreb, Croatia, in September 2008. The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the second volume are artificial intelligence driven engineering design optimization; biomedical informatics: intelligent information management from nanomedicine to public health; communicative intelligence; computational intelligence for image processing and pattern recognition; computational intelligence in human cancer research; computational intelligence techniques for Web personalization; computational intelligent techniques for bioprocess modelling, monitoring and control; intelligent computing for Grid; intelligent security techniques; intelligent utilization of soft computing techniques; reasoning-based intelligent systems: relevant reasoning for discovery and prediction; spatio-temporal database concept support for organizing virtual earth; advanced knowledge-based systems; chance discovery; innovation-oriented knowledge management platform; knowledge-based creativity support systems; knowledge-based interface systems; knowledge-based multi-criteria decision support; and knowledge-based systems for e-business.

Book Advances in Knowledge Discovery and Data Mining

Download or read book Advances in Knowledge Discovery and Data Mining written by Joshua Zhexue Huang and published by Springer Science & Business Media. This book was released on 2011-05-09 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knoweldge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.

Book Inductive Logic Programming

    Book Details:
  • Author : Tamas Horváth
  • Publisher : Springer Science & Business Media
  • Release : 2003-09-24
  • ISBN : 3540201440
  • Pages : 411 pages

Download or read book Inductive Logic Programming written by Tamas Horváth and published by Springer Science & Business Media. This book was released on 2003-09-24 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Inductive Logic Programming, ILP 2003, held in Szeged, Hungary in September/October 2003. The 23 revised full papers presented were carefully reviewed and selected from 53 submissions. Among the topics addressed are multirelational data mining, complexity issues, theory revision, clustering, mathematical discovery, relational reinforcement learning, multirelational learning, inductive inference, description logics, grammar systems, and inductive learning.