Computational learning theory and natural learning systems: 1 Constraints and prospects
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. u.a.
MIT Press
1994
|
| Schriftenreihe: | A Bradford book
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XII, 565 S graph. Darst. |
| ISBN: | 0262581264 |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1804124048397959168 |
|---|---|
| adam_text | Contents
Preface
vii
Introduction
ix
I FOUNDATIONS
1
1
Logic and Learning
3
Daniel
N.
Osherson, Michael
Stob,
and Scott
Weinstein
2
Learning Theoretical Terms
25
Ranan B. Banerji
3
How Loading Complexity is Affected by Node Function Sets
49
Stephen Judd
4
Defining the Limits of Analogical Planning
65
Diane J. Cook
II REPRESENTATION AND BIAS
81
5
Learning Hard Concepts through Constructive Induction:
83
Framework and Rationale
Larry
Rendeli
and Raj Seshu
6
Learning Disjunctive Concepts Using Domain Knowledge
143
Harish Ragavan and Larry
Rendeli
7
Learning in an Abstraction Space
163
George Drastal
8
Binary Decision Trees and an Average-Case Model for
213
Concept Learning: Implications for Feature Construction
and the Study of Bias
Raj Seshu
9
Refining Algorithms with Knowledge-Based Neural
249
Networks: Improving the Chou-Fasman Algorithm for
Protein Folding
Richard
Maciin
and
Jude
W.
Shavlik
III SAMPLING PROBLEMS
287
10
Efficient Distribution-free Learning of Probabilistic Concepts
289
Michael J. Kearns and Robert E. Schapire
Contents
11 VC Dimension
and Sampling Complexity of Learning
331
Sparse Polynomials and Rational Functions
Marek Karpinski
and
Thorsten
Werther
12
Learning from Data with Bounded Inconsistency:
355
Theoretical and Experimental Results
Haym Hirsh and William W. Cohen
13
How Fast Can a Threshold Gate Learn?
381
Wolfgang Maass and
György
Turan
14
When Are fc-Nearest Neighbor and Backpropagation
415
Accurate for Feasible-sized Sets of Examples?
Eric B.
Baum
IV EXPERIMENTAL
443
15
Comparing Connectionist and Symbolic Learning Methods
445
J. R. Quinlan
16
Weight Elimination and Effective Network Size
457
Andreas S. Weigend and David E. Rumelhart
17
Simulation Results for a New Two-armed Bandit Heuristic
477
Ronald L. Rivest and Yiqun Yin
18
Hard Questions about Easy Tasks: Issues from Learning to
487
Play Games
Susan L. Epstein
19
Experiments on the Transfer of Knowledge between
523
Neural Networks
Lorien Y.
Pratt
Contributors
561
Index
563
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| id | DE-604.BV009700807 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T17:39:28Z |
| institution | BVB |
| isbn | 0262581264 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-006417077 |
| oclc_num | 257475086 |
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| physical | XII, 565 S graph. Darst. |
| publishDate | 1994 |
| publishDateSearch | 1994 |
| publishDateSort | 1994 |
| publisher | MIT Press |
| record_format | marc |
| series2 | A Bradford book |
| spelling | Computational learning theory and natural learning systems 1 Constraints and prospects ed. by Stephen José Hanson ... Cambridge, Mass. u.a. MIT Press 1994 XII, 565 S graph. Darst. txt rdacontent n rdamedia nc rdacarrier A Bradford book Mathematische Lerntheorie (DE-588)4169103-9 gnd rswk-swf (DE-588)1071861417 Konferenzschrift gnd-content Mathematische Lerntheorie (DE-588)4169103-9 s DE-604 Hanson, Stephen J. Sonstige oth (DE-604)BV009700800 1 Digitalisierung TU Muenchen application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006417077&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Computational learning theory and natural learning systems Mathematische Lerntheorie (DE-588)4169103-9 gnd |
| subject_GND | (DE-588)4169103-9 (DE-588)1071861417 |
| title | Computational learning theory and natural learning systems |
| title_auth | Computational learning theory and natural learning systems |
| title_exact_search | Computational learning theory and natural learning systems |
| title_full | Computational learning theory and natural learning systems 1 Constraints and prospects ed. by Stephen José Hanson ... |
| title_fullStr | Computational learning theory and natural learning systems 1 Constraints and prospects ed. by Stephen José Hanson ... |
| title_full_unstemmed | Computational learning theory and natural learning systems 1 Constraints and prospects ed. by Stephen José Hanson ... |
| title_short | Computational learning theory and natural learning systems |
| title_sort | computational learning theory and natural learning systems constraints and prospects |
| topic | Mathematische Lerntheorie (DE-588)4169103-9 gnd |
| topic_facet | Mathematische Lerntheorie Konferenzschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006417077&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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