LEADER 06273nam 22007935 450 001 9910767574803321 005 20200703071129.0 010 $a3-540-45583-3 024 7 $a10.1007/3-540-45583-3 035 $a(CKB)1000000000211621 035 $a(SSID)ssj0000321173 035 $a(PQKBManifestationID)11238201 035 $a(PQKBTitleCode)TC0000321173 035 $a(PQKBWorkID)10263830 035 $a(PQKB)11668680 035 $a(DE-He213)978-3-540-45583-7 035 $a(MiAaPQ)EBC3071523 035 $a(PPN)155174169 035 $a(EXLCZ)991000000000211621 100 $a20121227d2001 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAlgorithmic Learning Theory $e12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001. Proceedings. /$fedited by Naoki Abe, Roni Khardon, Thomas Zeugmann 205 $a1st ed. 2001. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2001. 215 $a1 online resource (XII, 388 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v2225 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-42875-5 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aEditors? 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. 330 $aThis volume contains the papers presented at the 12th Annual Conference on Algorithmic Learning Theory (ALT 2001), which was held in Washington DC, USA, during November 25?28, 2001. The main objective of the conference is to provide an inter-disciplinary forum for the discussion of theoretical foundations of machine learning, as well as their relevance to practical applications. The conference was co-located with the Fourth International Conference on Discovery Science (DS 2001). The volume includes 21 contributed papers. These papers were selected by the program committee from 42 submissions based on clarity, signi?cance, o- ginality, and relevance to theory and practice of machine learning. Additionally, the volume contains the invited talks of ALT 2001 presented by Dana Angluin of Yale University, USA, Paul R. Cohen of the University of Massachusetts at Amherst, USA, and the joint invited talk for ALT 2001 and DS 2001 presented by Setsuo Arikawa of Kyushu University, Japan. Furthermore, this volume includes abstracts of the invited talks for DS 2001 presented by Lindley Darden and Ben Shneiderman both of the University of Maryland at College Park, USA. The complete versions of these papers are published in the DS 2001 proceedings (Lecture Notes in Arti?cial Intelligence Vol. 2226). 410 0$aLecture Notes in Artificial Intelligence ;$v2225 606 $aComputer programming 606 $aArtificial intelligence 606 $aComputers 606 $aAlgorithms 606 $aMathematical logic 606 $aNatural language processing (Computer science) 606 $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 615 0$aComputer programming. 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aAlgorithms. 615 0$aMathematical logic. 615 0$aNatural language processing (Computer science). 615 14$aProgramming Techniques. 615 24$aArtificial Intelligence. 615 24$aComputation by Abstract Devices. 615 24$aAlgorithm Analysis and Problem Complexity. 615 24$aMathematical Logic and Formal Languages. 615 24$aNatural Language Processing (NLP). 676 $a005.1 702 $aAbe$b Naoki$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKhardon$b Roni$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZeugmann$b Thomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aALT 2001 906 $aBOOK 912 $a9910767574803321 996 $aAlgorithmic Learning Theory$9771965 997 $aUNINA