06273nam 22007935 450 991076757480332120200703071129.03-540-45583-310.1007/3-540-45583-3(CKB)1000000000211621(SSID)ssj0000321173(PQKBManifestationID)11238201(PQKBTitleCode)TC0000321173(PQKBWorkID)10263830(PQKB)11668680(DE-He213)978-3-540-45583-7(MiAaPQ)EBC3071523(PPN)155174169(EXLCZ)99100000000021162120121227d2001 u| 0engurnn|008mamaatxtccrAlgorithmic Learning Theory 12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001. Proceedings. /edited by Naoki Abe, Roni Khardon, Thomas Zeugmann1st ed. 2001.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2001.1 online resource (XII, 388 p.) Lecture Notes in Artificial Intelligence ;2225Bibliographic Level Mode of Issuance: Monograph3-540-42875-5 Includes bibliographical references at the end of each chapters and index.Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- The Discovery Science Project in Japan -- Queries Revisited -- Robot Baby 2001 -- Discovering Mechanisms: A Computational Philosophy of Science Perspective -- Inventing Discovery Tools: Combining Information Visualization with Data Mining -- Complexity of Learning -- On Learning Correlated Boolean Functions Using Statistical Queries (Extended Abstract) -- A Simpler Analysis of the Multi-way Branching Decision Tree Boosting Algorithm -- Minimizing the Quadratic Training Error of a Sigmoid Neuron Is Hard -- Support Vector Machines -- Learning of Boolean Functions Using Support Vector Machines -- A Random Sampling Technique for Training Support Vector Machines -- New Learning Models -- Learning Coherent Concepts -- Learning Intermediate Concepts -- Real-Valued Multiple-Instance Learning with Queries -- Online Learning -- Loss Functions, Complexities, and the Legendre Transformation -- Non-linear Inequalities between Predictive and Kolmogorov Complexities -- Inductive Inference -- Learning by Switching Type of Information -- Learning How to Separate -- Learning Languages in a Union -- On the Comparison of Inductive Inference Criteria for Uniform Learning of Finite Classes -- Refutable Inductive Inference -- Refutable Language Learning with a Neighbor System -- Learning Recursive Functions Refutably -- Refuting Learning Revisited -- Learning Structures and Languages -- Efficient Learning of Semi-structured Data from Queries -- Extending Elementary Formal Systems -- Learning Regular Languages Using RFSA -- Inference of ?-Languages from Prefixes.This volume contains the papers presented at the 12th Annual Conference on Algorithmic Learning Theory (ALT 2001), which was held in Washington DC, USA, during November 25–28, 2001. The main objective of the conference is to provide an inter-disciplinary forum for the discussion of theoretical foundations of machine learning, as well as their relevance to practical applications. The conference was co-located with the Fourth International Conference on Discovery Science (DS 2001). The volume includes 21 contributed papers. These papers were selected by the program committee from 42 submissions based on clarity, signi?cance, o- ginality, and relevance to theory and practice of machine learning. Additionally, the volume contains the invited talks of ALT 2001 presented by Dana Angluin of Yale University, USA, Paul R. Cohen of the University of Massachusetts at Amherst, USA, and the joint invited talk for ALT 2001 and DS 2001 presented by Setsuo Arikawa of Kyushu University, Japan. Furthermore, this volume includes abstracts of the invited talks for DS 2001 presented by Lindley Darden and Ben Shneiderman both of the University of Maryland at College Park, USA. The complete versions of these papers are published in the DS 2001 proceedings (Lecture Notes in Arti?cial Intelligence Vol. 2226).Lecture Notes in Artificial Intelligence ;2225Computer programmingArtificial intelligenceComputersAlgorithmsMathematical logicNatural language processing (Computer science)Programming Techniqueshttps://scigraph.springernature.com/ontologies/product-market-codes/I14010Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Computation by Abstract Deviceshttps://scigraph.springernature.com/ontologies/product-market-codes/I16013Algorithm Analysis and Problem Complexityhttps://scigraph.springernature.com/ontologies/product-market-codes/I16021Mathematical Logic and Formal Languageshttps://scigraph.springernature.com/ontologies/product-market-codes/I16048Natural Language Processing (NLP)https://scigraph.springernature.com/ontologies/product-market-codes/I21040Computer programming.Artificial intelligence.Computers.Algorithms.Mathematical logic.Natural language processing (Computer science).Programming Techniques.Artificial Intelligence.Computation by Abstract Devices.Algorithm Analysis and Problem Complexity.Mathematical Logic and Formal Languages.Natural Language Processing (NLP).005.1Abe Naokiedthttp://id.loc.gov/vocabulary/relators/edtKhardon Roniedthttp://id.loc.gov/vocabulary/relators/edtZeugmann Thomasedthttp://id.loc.gov/vocabulary/relators/edtALT 2001BOOK9910767574803321Algorithmic Learning Theory771965UNINA05384nam 2200613 a 450 991087778720332120200520144314.01-282-24272-597866138138481-118-03260-81-118-03085-0(CKB)2670000000077521(EBL)675053(SSID)ssj0000483481(PQKBManifestationID)11303500(PQKBTitleCode)TC0000483481(PQKBWorkID)10529328(PQKB)10784247(MiAaPQ)EBC675053(OCoLC)711780368(EXLCZ)99267000000007752119950411d1996 uy 0engur|n|---|||||txtccrComputer-aided analysis of difference schemes for partial differential equations /Victor G. Ganzha, E.V. VorozhtsovNew York John Wiley & Sons, Inc.c19961 online resource (476 p.)"A Wiley-Interscience publication."0-471-12946-1 Includes bibliographical references and index.Computer-Aided Analysis of Difference Schemes for Partial Differential Equations; Contents; Preface; 1 The Necessary Basics from the Stability Theory of Difference Schemes and Polynomials; 1.1 Preliminary Discussion of Stability and Approximation; 1.2 Computer Algebra Systems; 1.3 A Brief Review of the Contents of Chapters; 1.4 Stability, Approximation, and Convergence; 1.5 A Survey of Methods for the Stability Analysis of Difference Schemes; 1.5.1 Von Neumann Stability Analysis; 1.5.2 Differential Approximation Method; 1.5.3 Method of Frozen Coefficients1.6 Algebraic Criteria for Localization of Polynomial Zeros1.6.1 Similarity and Dimensional Considerations; 1.6.2 Liénard-Chipart Criterion; 1.6.3 Generalized Routh-Hurwitz Problem for the Characteristic Polynomial; 1.7 Determination of the Maximal Time Step from Stability Analysis Results; 1.7.1 The Use of the Least Squares Method; 1.7.2 A Method Based on the Requirement of a Constant Volume of a Cell of a Spatial Computing Mesh; 1.7.3 The Use of the Tables of the Coordinates of Points of Stability Region Boundaries; 1.8 On the Choice of Nondimensional Complexes; 1.9 Bibliographical Notes1.9.1 Historical Note on Stability Theories1.9.2 Application of Algebraic Criteria to Stability Analyses; 1.9.3 Use of Computer Algebra for the Automation of Certain Stages of the Stability Analyses; References; 2 Symbolic-Numerical Method for the Stability Investigation of Difference Schemes on a Computer; 2.1 General Structure of the Symbolic-Numerical Method; 2.2 The Case of Diagonalizable Amplification Matrices; 2.3 Scheme Checker; 2.4 Symbolic Stages of the Method; 2.5 Generation of a FORTRAN Program by Computer Algebra2.6 Computation of the Coordinates of Points of a Stability Region Boundary2.6.1 Use of the Bisection Method; 2.6.2 Automatic Determination of the Number of Spectral Grid Points; 2.7 Improved Accuracy of Numerical Results; 2.7.1 Scaling in the Routh Algorithm; 2.7.2 Scaling in the Routh-Hurwitz Algorithm; 2.8 Examples of Stability Analyses of Difference Schemes for Equations of Hyperbolic Type; 2.8.1 Two-Step Richtmyer's Form of the Lax-Wendroff Scheme; 2.8.2 MacCormack Scheme for the Two-Dimensional Advection Equation; 2.8.3 Jameson's Schemes2.9 Stability Analysis of the MacCormack Scheme for Two-Dimensional Euler Equations2.10 Stability Analysis of the MacCormack Scheme for Three-Dimensional Euler Equations; 2.11 Examples of Stability Analyses of Difference Schemes for Navier-Stokes Equations; 2.11.1 A Family of Schemes for One-Dimensional Navier-Stokes Equations; 2.11.2 Difference Schemes on Curvilinear Grids; References; 3 Application of Optimization Methods to the Stability Analysis of Difference Schemes; 3.1 Formulation of a Search for Stability Region Boundaries of Difference Schemes in Terms of Optimization Theory3.1.1 The Case of One Nondimensional ComplexAdvances in computer technology have conveniently coincided with trends in numerical analysis toward increased complexity of computational algorithms based on finite difference methods. It is no longer feasible to perform stability investigation of these methods manually--and no longer necessary. As this book shows, modern computer algebra tools can be combined with methods from numerical analysis to generate programs that will do the job automatically.Comprehensive, timely, and accessible--this is the definitive reference on the application of computerized symbolic manipulations for aDifferential equations, PartialNumerical solutionsData processingFinite differencesData processingDifferential equations, PartialNumerical solutionsData processing.Finite differencesData processing.515/.353Ganzha V. G(Victor Grigorevich),1956-30381Vorozhtsov E. V(Evgenii Vasilevich),1946-30382MiAaPQMiAaPQMiAaPQBOOK9910877787203321Computer-aided analysis of difference schemes for partial differential equations4203122UNINA