04916nam 22007695 450 991014402880332120200701231516.03-540-39624-110.1007/b14273(CKB)1000000000212225(SSID)ssj0000321175(PQKBManifestationID)11247372(PQKBTitleCode)TC0000321175(PQKBWorkID)10263622(PQKB)10983029(DE-He213)978-3-540-39624-6(MiAaPQ)EBC3087723(PPN)155202111(EXLCZ)99100000000021222520121227d2003 u| 0engurnn|008mamaatxtccrAlgorithmic Learning Theory 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings /edited by Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto1st ed. 2003.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2003.1 online resource (XII, 320 p.) Lecture Notes in Artificial Intelligence ;2842Bibliographic Level Mode of Issuance: Monograph3-540-20291-9 Includes bibliographical references at the end of each chapters and index.Invited 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.Lecture Notes in Artificial Intelligence ;2842Artificial intelligenceComputersAlgorithmsMathematical logicNatural language processing (Computer science)Artificial 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/I21040Artificial intelligence.Computers.Algorithms.Mathematical logic.Natural language processing (Computer science).Artificial Intelligence.Computation by Abstract Devices.Algorithm Analysis and Problem Complexity.Mathematical Logic and Formal Languages.Natural Language Processing (NLP).006.3/1Gavaldà Ricardedthttp://id.loc.gov/vocabulary/relators/edtJantke Klaus Pedthttp://id.loc.gov/vocabulary/relators/edtTakimoto Eijiedthttp://id.loc.gov/vocabulary/relators/edtALT 2003MiAaPQMiAaPQMiAaPQBOOK9910144028803321Algorithmic Learning Theory771965UNINA