LEADER 01123nas 2200361-- 450 001 9910896691703321 005 20180819085427.7 011 $a2390-2175 035 $a(OCoLC)4845741 035 $a(CKB)991042746878612 035 $a(CONSER)sn-86009735- 035 $a(EXLCZ)99991042746878612 100 $a20790411a19729999 -a- a 101 0 $afre 200 10$aAnnales de L'Institut national agronomique 210 $aAlger$cMinistère de l'enseignement supérieur et de la recherche scientifique 311 $a0373-0816 531 0 $aAnn. inst. nat. agron. 606 $aagriculture$zAlgeria$vPeriodicals 606 $aAgriculture$zAlgeria$vPeriodicals 606 $aAgriculture$vPeriodicals 606 $aAgriculture$2fast$3(OCoLC)fst00801355 607 $aAlgeria$2fast 608 $aPeriodicals.$2fast 615 3$aagriculture 615 0$aAgriculture 615 0$aAgriculture 615 7$aAgriculture. 712 02$aAlgeria.$bWiz?rat al-Ta?l?m al-??l?. 906 $aJOURNAL 912 $a9910896691703321 996 $aAnnales de l'Institut National Agronomique$9801527 997 $aUNINA LEADER 05314nam 22006615 450 001 9910484808303321 005 20251226195554.0 010 $a3-540-75225-0 024 7 $a10.1007/978-3-540-75225-7 035 $a(CKB)1000000000490295 035 $a(SSID)ssj0000316159 035 $a(PQKBManifestationID)11273109 035 $a(PQKBTitleCode)TC0000316159 035 $a(PQKBWorkID)10263460 035 $a(PQKB)10587893 035 $a(DE-He213)978-3-540-75225-7 035 $a(MiAaPQ)EBC3062714 035 $a(MiAaPQ)EBC6413229 035 $a(PPN)12372855X 035 $a(MiAaPQ)EBC337118 035 $a(EXLCZ)991000000000490295 100 $a20100301d2007 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAlgorithmic Learning Theory $e18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings /$fedited by Marcus Hutter, Rocco A. Servedio, Eiji Takimoto 205 $a1st ed. 2007. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2007. 215 $a1 online resource (XI, 406 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v4754 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-75224-2 320 $aIncludes bibliographical references and index. 327 $aEditors? Introduction -- Editors? Introduction -- Invited Papers -- A Theory of Similarity Functions for Learning and Clustering -- Machine Learning in Ecosystem Informatics -- Challenge for Info-plosion -- A Hilbert Space Embedding for Distributions -- Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity -- Invited Papers -- Feasible Iteration of Feasible Learning Functionals -- Parallelism Increases Iterative Learning Power -- Prescribed Learning of R.E. Classes -- Learning in Friedberg Numberings -- Complexity Aspects of Learning -- Separating Models of Learning with Faulty Teachers -- Vapnik-Chervonenkis Dimension of Parallel Arithmetic Computations -- Parameterized Learnability of k-Juntas and Related Problems -- On Universal Transfer Learning -- Online Learning -- Tuning Bandit Algorithms in Stochastic Environments -- Following the Perturbed Leader to Gamble at Multi-armed Bandits -- Online Regression Competitive with Changing Predictors -- Unsupervised Learning -- Cluster Identification in Nearest-Neighbor Graphs -- Multiple Pass Streaming Algorithms for Learning Mixtures of Distributions in -- Language Learning -- Learning Efficiency of Very Simple Grammars from Positive Data -- Learning Rational Stochastic Tree Languages -- Query Learning -- One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples -- Polynomial Time Algorithms for Learning k-Reversible Languages and Pattern Languages with Correction Queries -- Learning and Verifying Graphs Using Queries with a Focus on Edge Counting -- Exact Learning of Finite Unions of Graph Patterns from Queries -- Kernel-Based Learning -- Polynomial Summaries of Positive Semidefinite Kernels -- Learning Kernel Perceptrons on Noisy Data Using Random Projections -- Continuityof Performance Metrics for Thin Feature Maps -- Other Directions -- Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability -- Pseudometrics for State Aggregation in Average Reward Markov Decision Processes -- On Calibration Error of Randomized Forecasting Algorithms. 330 $aThis volume contains the papers presented at the 18th International Conf- ence on Algorithmic Learning Theory (ALT 2007), which was held in Sendai (Japan) during October 1?4, 2007. The main objective of the conference was to provide an interdisciplinary forum for high-quality talks with a strong theore- cal background and scienti?c interchange in areas such as query models, on-line learning, inductive inference, algorithmic forecasting, boosting, support vector machines, kernel methods, complexity and learning, reinforcement learning, - supervised learning and grammatical inference. The conference was co-located with the Tenth International Conference on Discovery Science (DS 2007). This volume includes 25 technical contributions that were selected from 50 submissions by the ProgramCommittee. It also contains descriptions of the ?ve invited talks of ALT and DS; longer versions of the DS papers are available in the proceedings of DS 2007. These invited talks were presented to the audience of both conferences in joint sessions. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v4754 606 $aArtificial intelligence 606 $aData mining 606 $aArtificial Intelligence 606 $aData Mining and Knowledge Discovery 615 0$aArtificial intelligence. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 676 $a005.1 702 $aHutter$b Marcus 702 $aServedio$b Rocco A. 702 $aTakimoto$b Eiji$f1964- 712 12$aALT 2007 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484808303321 996 $aAlgorithmic Learning Theory$9771965 997 $aUNINA