Proceedings of the Sixth International Workshop on Machine Learning, Cornell University, Ithaca, New York, June 26-27, 1989 /

Machine Learning Proceedings 1989.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: International Workshop on Machine Learning Cornell University
Otros Autores: Segre, Alberto Maria
Formato: Electrónico Congresos, conferencias eBook
Idioma:Inglés
Publicado: San Mateo, Calif. : M. Kaufmann Publishers, �1989.
Temas:
Machine learning > Congresses.
Apprentissage automatique > Congr�es.
Machine learning.
Lernender Automat
Lernender Automat.
Congress
Conference papers and proceedings.
Actes de congr�es.
Kongress.
Acceso en línea:Texto completo

MARC

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111 2 |a International Workshop on Machine Learning  |n (6th :  |d 1989 :  |c Cornell University) 
245 1 0 |a Proceedings of the Sixth International Workshop on Machine Learning, Cornell University, Ithaca, New York, June 26-27, 1989 /  |c editor, workshop chair, Alberto Maria Segre. 
260 |a San Mateo, Calif. :  |b M. Kaufmann Publishers,  |c �1989. 
300 |a 1 online resource (ix, 510 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 
504 |a Includes bibliographical references and index. 
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 2010.  |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 
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588 0 |a Print version record. 
505 0 |a Front Cover; Proceedings of the Sixth International Workshop on Machine Learning; Copyright Page; Table of Contents; PREFACE; Part 1: Combining Empirical and Explanation-Based Learning; Chapter1. Unifying Themes in Empirical and Explanation-Based Learning; The Need for Unified Theories of Learning; Learning from One Instance and Many Instances; Learning With and Without Search; Learning With and Without Domain Knowledge; Justified and Unjustified Learning; Accuracy and Efficiency in Machine Learning 
505 8 |a CHAPTER2. INDUCTION OVER THE UNEXPLAINED: Integrated Learning of Concepts with Both Explainable and Conventional AspectsABSTRACT; INTRODUCTION; THE IOU APPROACH; AN INITIAL IOU ALGORITHM; IOU VERSUS PURE SBL AND IOE; CONCLUSIONS AND FUTURE RESEARCH; CHAPTER3. CONCEPTUAL CLUSTERING OF EXPLANATIONS; INDUCTION-BASED AND EXPLANATION-BASED LEARNING; OPEN PROBLEMS; CONCEPTUAL CLUSTERING OF EXPLANATIONS; CONCLUDING REMARKS; References; Chapter4. A Tight Integration of Deductive and Inductive Learning; 1 Introduction; 2 A new integration framework: generalized explanations; 3 An application example 
505 8 |a INTRODUCTIONINFERRING IN STRUCTOR'S GOAL; INFERRING PLACE IN CURRENT DIAGNOSIS; ADJUSTING THE SALIENCE OF FEATURES; CAUSAL EXPLANATION OF ACTIONS; CONCLUSION; References; CHAPTER 8. DEDUCTION IN TOP-DOWN INDUCTIVE LEARNING; References; CHAPTER 9. ONE-SIDED ALGORITHMS FOR INTEGRATING EMPIRICAL AND EXPLANATION-BASED LEARNING; A FRAMEWORK FOR INTEGRATED LEARNING; PERFORMANCE AND FOUNDATIONAL EXAMPLES; THE IOSC andk-IOSCNF ALGORITHM; CONCLUSION; References; CHAPTER 10. COMBINING EMPIRICAL AND ANALYTICAL LEARNING WITH VERSION SPACES; ABSTRACT; INTRODUCTION 
505 8 |a USING INCREMENTAL VERSION-SPACE MERGING ON THE RESULTS OF EBGPERSPECTIVES; RELATED WORK; SUMMARY; References; CHAPTER 11. FINDING NEW RULES FOR INCOMPLETE THEORIES: EXPLICIT BIASES FOR INDUCTION WITH CONTEXTUAL INFORMATION; INTRODUCTION; HEURISTICS EXPLOITING CONTEXTUAL INFORMATION AS A STRONG INDUCTIVE BIAS; EMPIRICAL SELECTION OF BIASES; CONCLUSION; Acknowledgments; REFERENCES; CHAPTER 12. LEARNING FROM PLAUSIBLE EXPLANATIONS; INTRODUCTION; THE LEARNING METHOD; CONCLUSION; References; CHAPTER 13. AUGMENTING DOMAIN THEORY FOR EXPLANATION-BASED GENERALISATION; INTRODUCTION 
520 |a Machine Learning Proceedings 1989. 
546 |a English. 
650 0 |a Machine learning  |v Congresses. 
650 6 |a Apprentissage automatique  |0 (CaQQLa)201-0131435  |v Congr�es.  |0 (CaQQLa)201-0378219 
650 7 |a Machine learning.  |2 fast  |0 (OCoLC)fst01004795 
650 7 |a Lernender Automat  |2 gnd  |0 (DE-588)4167398-0 
650 0 7 |a Lernender Automat.  |2 swd 
655 2 |a Congress  |0 (DNLM)D016423 
655 7 |a Conference papers and proceedings.  |2 fast  |0 (OCoLC)fst01423772 
655 7 |a Conference papers and proceedings.  |2 lcgft 
655 7 |a Actes de congr�es.  |2 rvmgf  |0 (CaQQLa)RVMGF-000001049 
655 7 |a Kongress.  |2 swd 
700 1 |a Segre, Alberto Maria. 
776 0 8 |i Print version:  |a International Workshop on Machine Learning (6th : 1989 : Cornell University).  |t Proceedings of the Sixth International Workshop on Machine Learning, Cornell University, Ithaca, New York, June 26-27, 1989.  |d San Mateo, Calif. : M. Kaufmann Publishers, �1989  |w (DLC) 89011110  |w (OCoLC)19741390 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9781558600362  |z Texto completo 

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