---
title: "Machine Learning 1991 — all accepted papers — Elamur Research"
description: "All 53 papers of Machine Learning 1991, the most cited first; those with our summary link to it."
canonical: "https://research.elamur.ai/free/en/venues/machine-learning/1991/papers/"
---
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# Machine Learning 1991: all accepted papers

53 papers · the most cited first · [← Machine Learning 1991](https://md.research.elamur.ai/free/en/venues/machine-learning/1991/)

1. **[Instance-Based Learning Algorithms](https://md.research.elamur.ai/free/en/papers/aha-1991-instance-based-learning-algorithms/)**David W. Aha, Dennis F. Kibler, Marc K. Albert*5,175 citations · our summary*
2. **[Distributed representations, simple recurrent networks, and grammatical structure ↗](https://doi.org/10.1007/bf00114844)**Jeffrey L. Elman*1,354 citations*
3. **[A Distance-Based Attribute Selection Measure for Decision Tree Induction ↗](https://doi.org/10.1023/a:1022694001379)**Ramón López de Mántaras*417 citations*
4. **[Letter Recognition Using Holland-Style Adaptive Classifiers ↗](https://doi.org/10.1007/bf00114162)**Peter W. Frey, David J. Slate*409 citations*
5. **[A Nearest Hyperrectangle Learning Method ↗](https://doi.org/10.1007/bf00114779)**Steven L. Salzberg*384 citations*
6. **[Symbolic and Neural Learning Algorithms: An Experimental Comparison ↗](https://doi.org/10.1007/bf00114160)**JUDE W. SHAVLIK, Raymond J. Mooney, Geoffrey G. Towell*327 citations*
7. **[Learning to Perceive and Act by Trial and Error ↗](https://doi.org/10.1007/bf00058926)**Steven D. Whitehead, Dana H. Ballard*300 citations*
8. **[The induction of dynamical recognizers ↗](https://doi.org/10.1007/bf00114845)**Jordan B. Pollack*294 citations*
9. **[Information-Based Evaluation Criterion for Classifier's Performance ↗](https://doi.org/10.1007/bf00153760)**Igor Kononenko, Ivan Bratko A*204 citations*
10. **[Graded state machines: The representation of temporal contingencies in simple recurrent networks ↗](https://doi.org/10.1007/bf00114843)**David Servan‐Schreiber, Axel Cleeremans, James L. McClelland*201 citations*
11. **[The Use of Background Knowledge in Decision Tree Induction ↗](https://doi.org/10.1023/a:1022609710832)**Marlon Núñez*196 citations*
12. **[The use of background knowledge in decision tree induction ↗](https://doi.org/10.1007/bf00114778)**Marlon N��ez*113 citations*
13. **[A distance-based attribute selection measure for decision tree induction ↗](https://doi.org/10.1007/bf00153761)**Ramon L�pez De M�ntaras*89 citations*
14. **[Improved Estimates for the Accuracy of Small Disjuncts ↗](https://doi.org/10.1007/bf00153762)**J. R. Quinlan*88 citations*
15. **[Complexity Results on Learning by Neural Nets ↗](https://doi.org/10.1007/bf00114777)**Jyh-Han Lin, Jeffrey Scott Vitter*85 citations*
16. **[Distributed Representations, Simple Recurrent Networks, And Grammatical Structure ↗](https://doi.org/10.1023/a:1022699029236)**Jeffrey L. Elman*83 citations*
17. **[Conflict Resolution as Discovery in Particle Physics ↗](https://doi.org/10.1007/bf00114780)**Șakir Kocabaș*81 citations*
18. **[Learning automata from ordered examples ↗](https://doi.org/10.1007/bf00114841)**Sara Porat, Jerome A. Feldman*56 citations*
19. **[A Critical Look at Experimental Evaluations of EBL ↗](https://doi.org/10.1007/bf00114163)**Alberto M. Segre, Charles Elkan, Alexander C. Russell*32 citations*
20. **[An Incremental Deductive Strategy for Controlling Constructive Induction in Learning from Examples ↗](https://doi.org/10.1007/bf00058925)**Renée Elio, Larry Watanabe*26 citations*
21. **[Rigel: An Inductive Learning System ↗](https://doi.org/10.1007/bf00153758)**Roberto Gemello, Franco Mana, Lorenza Saitta*19 citations*
22. **[The Induction of Dynamical Recognizers ↗](https://doi.org/10.1023/a:1022651113306)**Jordan B. Pollack*19 citations*
23. **[SLUG: A connectionist architecture for inferring the structure of finite-state environments ↗](https://doi.org/10.1007/bf00114842)**Michael C. Mozer, Jonathan R. Bachrach*15 citations*
24. **[Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks ↗](https://doi.org/10.1023/a:1022647012398)**David Servan‐Schreiber, Axel Cleeremans, James L. McClelland*12 citations*
25. **[Introduction ↗](https://doi.org/10.1023/a:1022668727419)**David S. Touretzky*10 citations*
26. **[Learning search control knowledge: An explanation-based approach ↗](https://doi.org/10.1007/bf00114164)**Roland J. Zito-Wolf*10 citations*
27. **[Exemplar-based knowledge acquisition ↗](https://doi.org/10.1007/bf00153763)**Yoram Reich*7 citations*
28. **[Learning to Predict Non-Deterministically Generated Strings ↗](https://doi.org/10.1007/bf00058927)**Moshe Koppel*4 citations*
29. **[Relational Clichés: Constraining Induction During Relational Learning. ↗](http://dblp.uni-trier.de/db/conf/icml/ml1991.html#SilversteinP91)**Glenn Silverstein, Michael J. Pazzani*4 citations*
30. **[Book Review: Exemplar-Based Knowledge Acquisition, by Ray Bareiss. Academic Press, 1989 ↗](https://doi.org/10.1023/a:1022698102287)**Yoram Reich*2 citations*
31. **[Learning Automata from Ordered Examples ↗](https://doi.org/10.1023/a:1022642911489)**Sara Porat, Jerome A. Feldman*2 citations*
32. **[Variable Resolution Dynamic Programming. ↗](http://dblp.uni-trier.de/db/conf/icml/ml1991.html#Moore91)**Andrew Moore*2 citations*
33. **[A ?PAC? algorithm for making feature maps ↗](https://doi.org/10.1007/bf00114161)**Philip D. Laird, Evan Gamble*1 citation*
34. **[Editorial ↗](https://doi.org/10.1007/bf00058924)***1 citation*
35. **[Generalizing the Learning Model ↗](https://doi.org/10.1016/b978-0-08-051053-8.50011-9)**BALAS K. NATARAJAN*1 citation*
36. **[Introduction ↗](https://doi.org/10.1007/bf00114840)***1 citation*
37. **[Learning Concepts on Countable Domains ↗](https://doi.org/10.1016/b978-0-08-051053-8.50005-3)**BALAS K. NATARAJAN*1 citation*
38. **[Learning Concepts on Uncountable Domains ↗](https://doi.org/10.1016/b978-0-08-051053-8.50007-7)**BALAS K. NATARAJAN*1 citation*
39. **[Learning Functions ↗](https://doi.org/10.1016/b978-0-08-051053-8.50008-9)**BALAS K. NATARAJAN*1 citation*
40. **[A Reply To Reich's Book Review of Exemplar-Based Knowledge Acquisition ↗](https://doi.org/10.1007/bf00153764)**Ray Bareiss
41. **[A Reply to Zito-Wolf's Book Review of Learning Search Control Knowledge: An Explanation-Based Approach ↗](https://doi.org/10.1023/a:1022662621851)**Steven Minton
42. **[A reply to Zito-Wolf's book review ofLearning search control knowledge: An explanation-based approach ↗](https://doi.org/10.1007/bf00114165)**
43. **[Book ReviewLearning Search Control Knowledge: An Explanation-Based Approach, by Steven Minton. Kluwer Academic Publishers, 1988, 214 pages ↗](https://doi.org/10.1023/a:1022610505013)**Roland J. Zito-Wolf
44. **[Conclusion ↗](https://doi.org/10.1016/b978-0-08-051053-8.50012-0)**BALAS K. NATARAJAN
45. **[Editorial ↗](https://doi.org/10.1023/a:1022665232329)**Jaime G. Carbonell
46. **[Editorial ↗](https://doi.org/10.1007/bf00153757)**Jaime G. Carbonell
47. **[Editorial ↗](https://doi.org/10.1023/a:1022615008686)**Jaime G. Carbonell
48. **[Finite Automata ↗](https://doi.org/10.1016/b978-0-08-051053-8.50009-0)**BALAS K. NATARAJAN
49. **[Introduction ↗](https://doi.org/10.1016/b978-0-08-051053-8.50004-1)**BALAS K. NATARAJAN
50. **[Neural Networks ↗](https://doi.org/10.1016/b978-0-08-051053-8.50010-7)**BALAS K. NATARAJAN
51. **[Notation ↗](https://doi.org/10.1016/b978-0-08-051053-8.50013-2)**
52. **[SLUG: A Connectionist Architecture for Inferring the Structure of Finite-State Environments ↗](https://doi.org/10.1023/a:1022694928327)**Michael C. Mozer, Jonathan R. Bachrach
53. **[Time Complexity of Concept Learning ↗](https://doi.org/10.1016/b978-0-08-051053-8.50006-5)**BALAS K. NATARAJAN
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