LEADER 03817oam 2200625 450 001 996465614103316 005 20210722144650.0 010 $a1-280-80456-4 010 $a9786610804566 010 $a3-540-46769-6 024 7 $a10.1007/3-540-46769-6 035 $a(CKB)1000000000211187 035 $a(EBL)3036569 035 $a(SSID)ssj0000288523 035 $a(PQKBManifestationID)11231401 035 $a(PQKBTitleCode)TC0000288523 035 $a(PQKBWorkID)10381275 035 $a(PQKB)10162948 035 $a(DE-He213)978-3-540-46769-4 035 $a(MiAaPQ)EBC3036569 035 $a(MiAaPQ)EBC6489632 035 $a(PPN)155189530 035 $a(EXLCZ)991000000000211187 100 $a20210722d1999 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAlgorithmic learning theory $e10th International Conference, ALT'99, Tokyo, Japan, December 6-8, 1999 : proceedings /$fOsamu Watanabe, Takashi Yokomori, eds 205 $a1st ed. 1999. 210 1$aBerlin, Germany ;$aNew York, New York :$cSpringer,$d[1999] 210 4$d©1999 215 $a1 online resource (374 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1720 300 $aDescription based upon print version of record. 311 $a3-540-66748-2 320 $aIncludes bibliographical references and index. 327 $aInvited Lectures -- Tailoring Representations to Different Requirements -- Theoretical Views of Boosting and Applications -- Extended Stochastic Complexity and Minimax Relative Loss Analysis -- Regular Contributions -- Algebraic Analysis for Singular Statistical Estimation -- Generalization Error of Linear Neural Networks in Unidentifiable Cases -- The Computational Limits to the Cognitive Power of the Neuroidal Tabula Rasa -- The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract) -- The VC-Dimension of Subclasses of Pattern Languages -- On the V ? Dimension for Regression in Reproducing Kernel Hilbert Spaces -- On the Strength of Incremental Learning -- Learning from Random Text -- Inductive Learning with Corroboration -- Flattening and Implication -- Induction of Logic Programs Based on ?-Terms -- Complexity in the Case Against Accuracy: When Building One Function-Free Horn Clause Is as Hard as Any -- A Method of Similarity-Driven Knowledge Revision for Type Specializations -- PAC Learning with Nasty Noise -- Positive and Unlabeled Examples Help Learning -- Learning Real Polynomials with a Turing Machine -- Faster Near-Optimal Reinforcement Learning: Adding Adaptiveness to the E3 Algorithm -- A Note on Support Vector Machine Degeneracy -- Learnability of Enumerable Classes of Recursive Functions from ?Typical? Examples -- On the Uniform Learnability of Approximations to Non-recursive Functions -- Learning Minimal Covers of Functional Dependencies with Queries -- Boolean Formulas Are Hard to Learn for Most Gate Bases -- Finding Relevant Variables in PAC Model with Membership Queries -- General Linear Relations among Different Types of Predictive Complexity -- Predicting Nearly as Well as the Best Pruning of a Planar Decision Graph -- On Learning Unions of Pattern Languages and Tree Patterns. 410 0$aLecture Notes in Artificial Intelligence ;$v1720 606 $aMachine learning$vCongresses 606 $aComputer algorithms$vCongresses 615 0$aMachine learning 615 0$aComputer algorithms 676 $a006.3/1 702 $aWatanabe$b Osamu$f1958- 702 $aYokomori$b Takashi 712 12$aALT'99 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a996465614103316 996 $aAlgorithmic Learning Theory$9771965 997 $aUNISA LEADER 00890nam a22002171i 4500 001 991000363889707536 005 20030130150440.0 008 021004s1900 it |||||||||||||||||ita 035 $ab11994605-39ule_inst 035 $aARCHE-008440$9ExL 040 $aDip.to Filologia Ling. e Lett.$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 100 1 $aPiglionica, Anna Maria$0449021 245 12$aL'oro come funzione drammatica in The comedy of errors /$cAnna Maria Piglionica 260 $aBari :$bAdriatica,$c1900 300 $a85 p. ;$c24 cm 907 $a.b11994605$b02-04-14$c01-04-03 912 $a991000363889707536 945 $aLE008 FL.M. (IN) B 53$g1$i2008000305017$lle008$o-$pE0.00$q-$rn$so $t0$u0$v0$w0$x0$y.i1227866x$z01-04-03 996 $aOro come funzione drammatica in The comedy of errors$9131285 997 $aUNISALENTO 998 $ale008$b01-04-03$cm$da $ew$fita$git $h2$i1