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Machine Learning 1986: all accepted papers

31 papers · the most cited first · ← Machine Learning 1986

  1. Induction of Decision Trees ↗J. R. Quinlan21,170 citations
  2. Explanation-Based Generalization: A Unifying View ↗Tom M. Mitchell, Richard M. Keller, Smadar T. Kedar-Cabelli1,174 citations
  3. Editorial: On Machine Learning ↗Pat Langley951 citations
  4. Explanation-Based Learning: An Alternative ViewGERALD F. DEJONG, Raymond J. Mooney950 citations · our summary
  5. Explanation-based generalization: A unifying view ↗Tom M. Mitchell, Richard M. Keller, Smadar T. Kedar-Cabelli711 citations
  6. Incremental Learning from Noisy Data ↗Jeffrey C. Schlimmer, Richard Granger653 citations
  7. Chunking in Soar: The Anatomy of a General Learning Mechanism ↗John E. Laird, Paul S. Rosenbloom, Allen Newell507 citations
  8. Chunking in Soar: The anatomy of a general learning mechanism ↗John E. Laird, Paul S. Rosenbloom, Allen Newell287 citations
  9. Learning at the Knowledge Level ↗Thomas G. Dietterich221 citations
  10. Integrating Quantitative and Qualitative Discovery: The ABACUS System ↗Brian C. Falkenhainer, Ryszard S. Michalski179 citations
  11. A General Framework for Induction and a Study of Selective Induction ↗Larry A. Rendell138 citations
  12. Escaping Brittleness : the Possibilities of General Purpose Learning Algorithms Applied to Parallel Rule-based System ↗John H. Holland121 citations
  13. Determining Arguments of Invariant Functional Descriptions ↗Mieczyslaw M. Kokar87 citations
  14. A Theory of Historical Discovery: The Construction of Componential Models ↗Jan M. Żytkow, Herbert A. Simon81 citations
  15. Chemical Discovery as Belief Revision ↗Donald Rose, Pat Langley74 citations
  16. Integrating quantitative and qualitative discovery: The ABACUS system ↗Brian C. Falkenhainer, Ryszard S. Michalski55 citations
  17. Integrating Qualitative and Quantitative Discovery : The ABACUS System ↗Brian C. Falkenhainer54 citations
  18. Experimental Goal Regression: A Method for Learning Problem-Solving Heuristics ↗Bruce Porter, Dennis F. Kibler44 citations
  19. Editorial: On machine learning ↗Pat Langley9 citations
  20. Editorial: Machine Learning and Discovery ↗Pat Langley, Ryszard S. Michalski5 citations
  21. News and Notes ↗4 citations
  22. Editorial: The Terminology of Machine Learning ↗Pat Langley3 citations
  23. Editorial: Machine learning and discovery ↗Pat Langley, Ryszard S. Michalski2 citations
  24. Editorial: The terminology of machine learning ↗Pat Langley2 citations
  25. Editorial: Human and Machine Learning ↗Pat Langley1 citation
  26. Editorial: Human and machine learning ↗Pat Langley1 citation
  27. News and Notes ↗Thomas G. Dietterich1 citation
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