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Machine Learning, Volume 4

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Volume 4, 1989

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Jaime G. Carbonell:
Editorial. Machine Learning 4: 5-6 (1989)
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David Haussler:
Learning Conjunctive Concepts in Structural Domains. 7-40
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Raymond A. Board, Leonard Pitt:
Semi-Supervised Learning. 41-65
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B. K. Natarajan:
On Learning Sets and Functions. 67-97
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Kurt VanLehn:
Efficient Specialization of Relational Concepts. 99-106
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  - journals/ml/Dietterich89a
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Thomas G. Dietterich:
News and Notes. Machine Learning 4: 107-109 (1989)
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Jaime G. Carbonell:
Editorial. 113-115
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Paul O'Rorke:
LT Revisited: Explanation-Based Learning and the Logic of Principia Mathematica. 117-159
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Paul E. Utgoff:
Incremental Induction of Decision Trees. 161-186
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Nicholas S. Flann, Thomas G. Dietterich:
A Study of Explanation-Based Methods for Inductive Learning. 187-226
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John Mingers:
An Empirical Comparison of Pruning Methods for Decision Tree Induction. 227-243
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Bruce G. Buchanan:
Can Machine Learning Offer Anything to Expert Systems? 251-254
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Douglas B. Lenat:
When Will Machines Learn? 255-257
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Ray Bareiss, Bruce W. Porter, Kenneth S. Murray:
Supporting Start-to-Finish Development of Knowledge Bases. 259-283
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William J. Clancey:
The Knowledge Level Reinterpreted: Modeling How Systems Interact. 285-291
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Thomas R. Gruber:
Automated Knowledge Acquisition for Strategic Knowledge. 293-336
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John P. McDermott:
The World Would Be a Better Place if Non-Programmers Could Program. Machine Learning 4: 337-338 (1989)
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B. Chandrasekaran:
Task-Structures, Knowledge Acquisition and Learning. 339-345
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Mark A. Musen:
Automated Support for Building and Extending Expert Models. 347-375
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John H. Boose, Brian R. Gaines:
Knowledge Acquisition for Knowledge-Based Systems: Notes on the State-of-the-Art. 377-394

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