LEADER 01166nas 2200397 c 450 001 9910143712003321 005 20171201122650.0 035 $a(CKB)1000000000532804 035 $a(DE-599)ZDB2432430-9 035 $a(OCoLC)723982539 035 $a(OCoLC)705294597 035 $a(DE-101)989223825 035 $a(EXLCZ)991000000000532804 100 $a20080617a20009999 |y | 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aWiener Library news$ethe newsletter of The Wiener Library, Institute of Contemporary History 210 31$aLondon$d2000- 215 $aOnline-Ressource 300 $aGesehen am 17.06.08 517 3 $a˜Theœ newsletter of The Wiener Library, Institute of Contemporary History 517 1 $aNewsletter 608 $aZeitschrift$2gnd-content 676 $a070 676 $a940 712 02$aInstitute of Contemporary History and Wiener Library$4isb 801 0$b0012 801 1$bDE-101 801 2$b9999 906 $aJOURNAL 912 $a9910143712003321 996 $aWiener Library news$91920526 997 $aUNINA LEADER 04633nam 2200589 450 001 996465373803316 005 20210312130026.0 010 $a3-540-87987-0 024 7 $a10.1007/978-3-540-87987-9 035 $a(CKB)1000000000490274 035 $a(SSID)ssj0000316160 035 $a(PQKBManifestationID)11273110 035 $a(PQKBTitleCode)TC0000316160 035 $a(PQKBWorkID)10263182 035 $a(PQKB)11715590 035 $a(DE-He213)978-3-540-87987-9 035 $a(MiAaPQ)EBC3063549 035 $a(MiAaPQ)EBC6413280 035 $a(PPN)13018554X 035 $a(EXLCZ)991000000000490274 100 $a20210312d2008 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aAlgorithmic learning theory $e19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, proceedings /$fYoav Freund [and three others], (Eds.) 205 $a1st ed. 2008. 210 1$aBerlin ;$aHeidelberg :$cSpringer,$d[2008] 210 4$d©2008 215 $a1 online resource (XIII, 467 p.) 225 1 $aLecture Notes in Computer Science ;$v5254 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-87986-2 320 $aIncludes bibliographical references and index. 327 $aInvited Papers -- On Iterative Algorithms with an Information Geometry Background -- Visual Analytics: Combining Automated Discovery with Interactive Visualizations -- Some Mathematics behind Graph Property Testing -- Finding Total and Partial Orders from Data for Seriation -- Computational Models of Neural Representations in the Human Brain -- Regular Contributions -- Generalization Bounds for Some Ordinal Regression Algorithms -- Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm -- Sample Selection Bias Correction Theory -- Exploiting Cluster-Structure to Predict the Labeling of a Graph -- A Uniform Lower Error Bound for Half-Space Learning -- Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces -- Learning and Generalization with the Information Bottleneck -- Growth Optimal Investment with Transaction Costs -- Online Regret Bounds for Markov Decision Processes with Deterministic Transitions -- On-Line Probability, Complexity and Randomness -- Prequential Randomness -- Some Sufficient Conditions on an Arbitrary Class of Stochastic Processes for the Existence of a Predictor -- Nonparametric Independence Tests: Space Partitioning and Kernel Approaches -- Supermartingales in Prediction with Expert Advice -- Aggregating Algorithm for a Space of Analytic Functions -- Smooth Boosting for Margin-Based Ranking -- Learning with Continuous Experts Using Drifting Games -- Entropy Regularized LPBoost -- Optimally Learning Social Networks with Activations and Suppressions -- Active Learning in Multi-armed Bandits -- Query Learning and Certificates in Lattices -- Clustering with Interactive Feedback -- Active Learning of Group-Structured Environments -- Finding the Rare Cube -- Iterative Learning of Simple External Contextual Languages -- Topological Properties of Concept Spaces -- Dynamically Delayed Postdictive Completeness and Consistency in Learning -- Dynamic Modeling in Inductive Inference -- Optimal Language Learning -- Numberings Optimal for Learning -- Learning with Temporary Memory -- Erratum: Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors. 330 $aThis book constitutes the refereed proceedings of the 19th International Conference on Algorithmic Learning Theory, ALT 2008, held in Budapest, Hungary, in October 2008, co-located with the 11th International Conference on Discovery Science, DS 2008. The 31 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 46 submissions. The papers are dedicated to the theoretical foundations of machine learning; they address topics such as statistical learning; probability and stochastic processes; boosting and experts; active and query learning; and inductive inference. 410 0$aLecture notes in computer science ;$v5254. 606 $aComputer algorithms$vCongresses 606 $aMachine learning$vCongresses 615 0$aComputer algorithms 615 0$aMachine learning 676 $a005.1 702 $aFreund$b Yoav 712 12$aALT 2008 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465373803316 996 $aAlgorithmic Learning Theory$9771965 997 $aUNISA