LEADER 04260nam 22005775 450 001 996466114403316 005 20200702130311.0 010 $a3-540-47470-6 024 7 $a10.1007/3-540-60454-5 035 $a(CKB)1000000000234357 035 $a(SSID)ssj0000321178 035 $a(PQKBManifestationID)11212656 035 $a(PQKBTitleCode)TC0000321178 035 $a(PQKBWorkID)10276822 035 $a(PQKB)10983518 035 $a(DE-He213)978-3-540-47470-8 035 $a(PPN)155187910 035 $a(EXLCZ)991000000000234357 100 $a20121227d1995 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAlgorithmic Learning Theory$b[electronic resource] $e6th International Workshop, ALT '95, Fukuoka, Japan, October 18 - 20, 1995. Proceedings /$fedited by Klaus P. Jantke, Takeshi Shinohara, Thomas Zeugmann 205 $a1st ed. 1995. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1995. 215 $a1 online resource (XV, 324 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v997 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-60454-5 327 $aGrammatical inference: An old and new paradigm -- Efficient learning of real time one-counter automata -- Learning strongly deterministic even linear languages from positive examples -- Language learning from membership queries and characteristic examples -- Learning unions of tree patterns using queries -- Inductive constraint logic -- Incremental learning of logic programs -- Learning orthogonal F-Horn formulas -- Learning nested differences in the presence of malicious noise -- Learning sparse linear combinations of basis functions over a finite domain -- Inferring a DNA sequence from erroneous copies (abstract) -- Machine induction without revolutionary paradigm shifts -- Probabilistic language learning under monotonicity constraints -- Noisy inference and oracles -- Simulating teams with many conjectures -- Complexity of network training for classes of Neural Networks -- Learning ordered binary decision diagrams -- Simple PAC learning of simple decision lists -- The complexity of learning minor closed graph classes -- Technical and scientific issues of KDD (or: Is KDD a science?) -- Analogical logic program synthesis algorithm that can refute inappropriate similarities -- Reflecting and self-confident inductive inference machines -- On approximately identifying concept classes in the limit -- Application of kolmogorov complexity to inductive inference with limited memory. 330 $aThis book constitutes the refereed proceedings of the 6th International Workshop on Algorithmic Learning Theory, ALT '95, held in Fukuoka, Japan, in October 1995. The book contains 21 revised full papers selected from 46 submissions together with three invited contributions. It covers all current areas related to algorithmic learning theory, in particular the theory of machine learning, design and analysis of learning algorithms, computational logic aspects, inductive inference, learning via queries, artificial and biologicial neural network learning, pattern recognition, learning by analogy, statistical learning, inductive logic programming, robot learning, and gene analysis. 410 0$aLecture Notes in Artificial Intelligence ;$v997 606 $aArtificial intelligence 606 $aComputers 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aTheory of Computation$3https://scigraph.springernature.com/ontologies/product-market-codes/I16005 615 0$aArtificial intelligence. 615 0$aComputers. 615 14$aArtificial Intelligence. 615 24$aTheory of Computation. 676 $a006.3/1 702 $aJantke$b Klaus P$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aShinohara$b Takeshi$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZeugmann$b Thomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aALT '95 906 $aBOOK 912 $a996466114403316 996 $aAlgorithmic Learning Theory$9771965 997 $aUNISA