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