LEADER 04941nam 22007695 450 001 996465796603316 005 20200701231516.0 010 $a3-540-39624-1 024 7 $a10.1007/b14273 035 $a(CKB)1000000000212225 035 $a(SSID)ssj0000321175 035 $a(PQKBManifestationID)11247372 035 $a(PQKBTitleCode)TC0000321175 035 $a(PQKBWorkID)10263622 035 $a(PQKB)10983029 035 $a(DE-He213)978-3-540-39624-6 035 $a(MiAaPQ)EBC3087723 035 $a(PPN)155202111 035 $a(EXLCZ)991000000000212225 100 $a20121227d2003 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAlgorithmic Learning Theory$b[electronic resource] $e14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings /$fedited by Ricard Gavaldą, Klaus P. Jantke, Eiji Takimoto 205 $a1st ed. 2003. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2003. 215 $a1 online resource (XII, 320 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v2842 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-20291-9 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aInvited Papers -- Abduction and the Dualization Problem -- Signal Extraction and Knowledge Discovery Based on Statistical Modeling -- Association Computation for Information Access -- Efficient Data Representations That Preserve Information -- Can Learning in the Limit Be Done Efficiently? -- Inductive Inference -- Intrinsic Complexity of Uniform Learning -- On Ordinal VC-Dimension and Some Notions of Complexity -- Learning of Erasing Primitive Formal Systems from Positive Examples -- Changing the Inference Type ? Keeping the Hypothesis Space -- Learning and Information Extraction -- Robust Inference of Relevant Attributes -- Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables -- Learning with Queries -- On the Learnability of Erasing Pattern Languages in the Query Model -- Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries -- Learning with Non-linear Optimization -- Kernel Trick Embedded Gaussian Mixture Model -- Efficiently Learning the Metric with Side-Information -- Learning Continuous Latent Variable Models with Bregman Divergences -- A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation -- Learning from Random Examples -- On the Complexity of Training a Single Perceptron with Programmable Synaptic Delays -- Learning a Subclass of Regular Patterns in Polynomial Time -- Identification with Probability One of Stochastic Deterministic Linear Languages -- Online Prediction -- Criterion of Calibration for Transductive Confidence Machine with Limited Feedback -- Well-Calibrated Predictions from Online Compression Models -- Transductive Confidence Machine Is Universal -- On the Existence and Convergence of Computable Universal Priors. 410 0$aLecture Notes in Artificial Intelligence ;$v2842 606 $aArtificial intelligence 606 $aComputers 606 $aAlgorithms 606 $aMathematical logic 606 $aNatural language processing (Computer science) 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)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aAlgorithms. 615 0$aMathematical logic. 615 0$aNatural language processing (Computer science). 615 14$aArtificial Intelligence. 615 24$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 $a006.3/1 702 $aGavaldą$b Ricard$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJantke$b Klaus P$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTakimoto$b Eiji$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aALT 2003 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465796603316 996 $aAlgorithmic Learning Theory$9771965 997 $aUNISA