Theory Refinement Combining Analytical and Empirical Methods (1994)

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by Dirk Ourston , Raymond Mooney
Venue:Artificial Intelligence
Citations:113 - 7 self

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14 Induction over the unexplained: Using overly-general domain theories to aid concept learning – Raymond J. Mooney - 1993
37 A multistrategy approach to theory refinement – Raymond J. Mooney, Dirk Ourston - 1991
7 Constructing New Attributes for Decision Tree Learning – Zijian Zheng - 1996
6 Feature Discovery for Inductive Concept Learning – Tom Fawcett - 1993
5 Integrating ILP and EBL – Raymond J. Mooney, John M. Zelle - 1994
1 Paradigms for Machine Learning – Jeffrey C. Schlimmer, Pat Langley - 1991
24 Transferring Previously Learned Back-Propagation Neural Networks To New Learning Tasks – L. Y. Pratt - 1993
3 Machine Learning: Techniques and Recent Developments – Peter Clark - 1990
18 Inductive Learning For Abductive Diagnosis – Cynthia A. Thompson, Raymond J. Mooney - 1994
11 The RISE 2.0 System: A Case Study in Multistrategy Learning – Pedro Domingos - 1995
4 On the Development of Inductive Learning Algorithms: Generating Flexible and Adaptable Concept Representations – Ricardo Vilalta - 1998
10 Combining Symbolic and Connectionist Learning Methods to Refine Certainty-Factor Rule-Bases – J. Jeffrey Mahoney - 1996
86 Unifying instance–based and rule–based induction – Pedro Domingos, J. Mooney - 1996
Machine Learning: An Annotated Bibliography for the 1995 AI & . . . – David W. Aha - 1995
69 Extracting Comprehensible Models from Trained Neural Networks – W. Craven - 1996
1 Learning Search-Control Heuristics for Logic Programs: Applications to Speedup Learning and Language Acquisition – John M. Zelle - 1993
6 Grammatically Biased Learning: Learning Horn Theories Using an Explicit Antecedent Description Language – William W. Cohen - 1991
6 Concept Acquisition by Autonomous Agents: Cognitive Modeling versus the Engineering Approach – Paul Davidsson - 1992
Encouraging Experimental Results on . . . – Raymond J. Mooney - 1995