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Machine learning : proceedings of the seventh international conference (1990), University of Texas, Austin, Texas, June 21-23, 1990 /
Machine Learning Proceedings 1990.
| Clasificación: | Libro Electrónico |
|---|---|
| Autores Corporativos: | , |
| Otros Autores: | , |
| Formato: | Electrónico Congresos, conferencias eBook |
| Idioma: | Inglés |
| Publicado: |
San Mateo, Calif. :
Morgan Kaufmann Publishers,
�1990.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 111 | 2 | |a International Conference on Machine Learning |n (7th : |d 1990 : |c University of Texas) | |
| 245 | 1 | 0 | |a Machine learning : |b proceedings of the seventh international conference (1990), University of Texas, Austin, Texas, June 21-23, 1990 / |c editor/workshop chairs, Bruce Porter and Raymond Mooney ; sponsors, Office of Naval Research, Artificial Intelligence and Robotics Program [and others]. |
| 264 | 1 | |a San Mateo, Calif. : |b Morgan Kaufmann Publishers, |c �1990. | |
| 300 | |a 1 online resource (v, 427 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a "Proceedings of the Seventh International Conference on Machine Learning"--Cover | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 1. Knowledge acquisition from examples usinmg maximal representation learning / S. Arun Kumar and S. Yegneshwar -- KBG: a knowledge based generalizer / G. Bisson -- Performance analysis of a probabalistic inductive learning system / K.C.C. Chan and A.K.C. Wong -- A comparative study of ID3 and backpropagation for English text-to-speech mapping / T.G. Dietterich, H. Hild, and G. Bakiri -- Learning from data with bounded inconsistency / H. Hirsh -- Conceptual set covering: improving fit-and-split algorithms / C.M. Kadie -- Incremental learning of rules and meta-rules / M. Schoenauer and M. Sebag -- An incremental method for finding multivariate splits for decision trees / P.E. Utgoff and C.E. Brodley -- Incremental induction of topologically minimal trees / W. Van de Velde. | |
| 505 | 0 | |a 2. A rational analysis of categorization / J.R. Anderson and M. Matessa -- Search control, utility, anf concept induction / B. Carlson, J. Weinberg, and D. Fisher -- Graph clustering and model learning by data compression / J. Segen -- 3. An analysis of representation shift in concept learning / W.E. Cohen -- Learning procedures by environment-driven constructive induction / D.V. Hume -- Beyond inversion of resolution / C. Rouveirol and J. Puget -- 4. Genetic programming / H. de Garis -- Improving the performance of genetic algorithms in automated discovery of parameters / N. Kadaba and K.E. Nygard -- Using genetic alogorithms to learn disjunctive rules from examples / R. Andrew McCallum and K.A. Spackman -- NEWBOOLE: a fast GBML system / P. Bonelli, A. Parodi, S. Sen and S. Wilson. | |
| 505 | 0 | |a 5. Learning functions in k-DNF from reinforcement / L.P. Kaelbling -- Is learning rate a good performance criterion for learning? / C. Sammut and J. Cribb -- Active perception and reinforcement learning / S.D. Whitehead and D.H. Ballard -- 6. Learning plans for competetive domains / S.L. Epstein -- Explanations of empirically derived reactive plans / D.F. Gordon and J.J. Grefenstette -- Learning and enforcement: stabilizing environments to facilitate activity / K.J. Hammond -- Simulation-assisted learning by competioion: effects of noise differences between training model and target environment / C.L. Ramsey, A.C. Schultz, and J.J. Grefenstette -- Integrated architecture for learning, planning, and reacting based on approximating dynamic programming / R.S. Sutton. | |
| 505 | 0 | |a 7. Reducing real-world failures of approximate explanation-based rules / S.W. Bennett -- Correcting and extending domain knowledge using outside guidance / J.E. Laird, M. Hucka, E.S. Yager, and C.M. Tuck -- Acquisition of dynamic control knowledge for a robotic manipulator / A.W. Moore -- Feature extraction and clustering of tactile impressions with connectionist models / M. Thint and P.P. Wang -- 8. Generalizing the order of goals as an approach to generalizing number / H. Bostrom -- Learning approximate control rules of high utility / W.W. Cohen -- Applying abstraction and simplification to learn in intratible domains / N.S. Fann -- Explanation-based learning with incomplete theories: a three-step approach / J. Genest, S. Matwin, and B. Plante -- Using abductive recovery of failed proofs for problem solving by analogy / Y. Kodratoff. | |
| 505 | 0 | |a Issues in the design of operator composition systems / S. Minton -- Incremental learning of explanation patterns and their indices / A. Ram -- 9. Integrated learning in a real domain / F. Bergadano, A. Giordana, L. Saitta, D. DeMarchi, and F. Brancadori -- Incremental version-space merging / H. Hirsch -- Average case analysis of conjunctive learning algorithms / M.J. Pazzani and W. Sarrett -- ILS: a framework for multi-paradigmatic learning / B. Silver, W. Frawley, G. Iba, J. Vittal, and K. Bradford -- An integrated framework of inducing rules from examples -- Y. WU, S. Wanf, and Q. Zhou -- 10. Adaptive parsing: a general method for learning idiosyncratic grammars / J.F. Lehman -- A comparison of learning techniques in second language learning / S.L. Lytinen and C.E. Moon -- Learning string patterns and tree patterns from examples -- K. Ko, A. Marron, and W. Tzeng. | |
| 505 | 0 | |a Learning with discrete multi-valued neurons / Z. Obradovic and I. Parberry -- 11. The general utility problems in machine learning / L.B. Holder -- A robust approach to numeric discovery / B. Nordhausen and P. Langley -- More results on the complexity of knowlegge base refinement: belief networks / M. Valtorta. | |
| 588 | 0 | |a Print version record. | |
| 520 | |a Machine Learning Proceedings 1990. | ||
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2011. |5 MiAaHDL | ||
| 538 | |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |u http://purl.oclc.org/DLF/benchrepro0212 |5 MiAaHDL | ||
| 583 | 1 | |a digitized |c 2011 |h HathiTrust Digital Library |l committed to preserve |2 pda |5 MiAaHDL | |
| 650 | 0 | |a Machine learning |v Congresses. | |
| 650 | 6 | |a Apprentissage automatique |0 (CaQQLa)201-0131435 |v Congr�es. |0 (CaQQLa)201-0378219 | |
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| 650 | 7 | |a Machine learning |2 fast |0 (OCoLC)fst01004795 | |
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| 653 | 0 | |a Machine learning |a Congresses | |
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| 700 | 1 | |a Porter, Bruce, |d 1956- | |
| 700 | 1 | |a Mooney, Raymond J. |q (Raymond Joseph) | |
| 710 | 2 | |a Artificial Intelligence and Robotics Program (U.S.) | |
| 776 | 0 | 8 | |i Print version: |a International Conference on Machine Learning (7th : 1990 : University of Texas). |t Machine learning |z 1558601414 |w (DLC) 90004763 |w (OCoLC)21599358 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9781558601413 |z Texto completo |