📰 Machine Learning 1995: all accepted papers

60 papers · the most cited first · ← Machine Learning 1995

1. Support-Vector NetworksCorinna Cortes, Vladimir N. Vapnik58,873 citations · our summary
2. Learning Bayesian Networks: The Combination of Knowledge and Statistical Data ↗David E. Heckerman, Dan Geiger, David M. Chickering3,231 citations
3. Learning Bayesian networks: The combination of knowledge and statistical data ↗David E. Heckerman, Dan Geiger, David M. Chickering2,017 citations
4. Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization ↗Timothy L. Bailey, Charles Elkan670 citations
5. Multivariate Decision Trees ↗Carla E. Brodley, Paul E. Utgoff447 citations
6. The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces ↗Andrew Moore, Christopher G. Atkeson259 citations
7. Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension ↗Sally Floyd, Manfred K. Warmuth256 citations
8. An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms ↗Dietrich Wettschereck, Thomas G. Dietterich239 citations
9. Monotonicity Maintenance in Information-Theoretic Machine Learning Algorithms ↗Arie Ben‐David164 citations
10. Automated Refinement of First-Order Horn-Clause Domain Theories ↗Bradley L. Richards, Raymond J. Mooney140 citations
11. Evaluation and Selection of Biases in Machine Learning ↗Diana F. Gordon, Marie Ellen Desjardins140 citations
12. The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces ↗Andrew Moore, Christopher G. Atkeson137 citations
13. Recursive Automatic Bias Selection for Classifier Construction ↗Carla E. Brodley126 citations
14. Technical note: Bias and the quantification of stability ↗Peter D. Turney121 citations
15. Genetic Algorithms, Operators, and DNA Fragment Assembly ↗Rebecca J. Parsons, Stephanie Forrest, Christian Burks110 citations
16. Neural Networks for Full-Scale Protein Sequence Classification: Sequence Encoding with Singular Value Decomposition ↗Cathy H. Wu, Michael W. Berry, Sailaja Shivakumar et al.99 citations
17. Inductive Policy: The Pragmatics of Bias Selection ↗Foster John Provost, Bruce G. Buchanan89 citations
18. ALECSYS and the AutonoMouse: Learning to Control a Real Robot by Distributed Classifier Systems ↗Marco Dorigo72 citations
19. Bounding the Vapnik-Chervonenkis dimension of concept classes parameterized by real numbers ↗Paul W. Goldberg, Mark Jerrum65 citations
20. A Comparison of ID3 and Backpropagation for English Text-To-Speech Mapping ↗Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri58 citations
21. Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning ↗Thomas Dean, Dana Angluin A, Kenneth Basye et al.52 citations
22. On Polynomial-Time Learnability in the Limit of Strictly Deterministic Automata ↗Takashi Yokomori42 citations
23. Piecemeal learning of an unknown environment ↗Margrit Betke, Ronald L. Rivest, Mona Singh41 citations
24. Declarative Bias for Specific-to-General ILP Systems ↗Hilde Adé, Luc De Raedt, Maurice Bruynooghe39 citations
25. Encouraging Experimental Results on Learning CNF ↗Raymond J. Mooney38 citations
26. On the Learnability of Disjunctive Normal Form Formulas ↗Howard Jay Aizenstein, Leonard Pitt34 citations
27. A comparison of ID3 and backpropagation for English text-to-speech mapping ↗Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri33 citations
28. The Appropriateness of Predicate Invention as Bias Shift Operation in ILP ↗Irene Stahl32 citations
29. Learning Binary Relations Using Weighted Majority Voting ↗Sally A. Goldman, Manfred K. Warmuth26 citations
30. Inferring finite automata with stochastic output functions and an application to map learning ↗Thomas Dean, Dana Angluin A, Kenneth Basye et al.25 citations
31. Learning Fallible Deterministic Finite Automata ↗Dana Ron, Ronitt Rubinfeld23 citations
32. Machine Discovery of Protein Motifs ↗Darrell Conklin20 citations
33. Discovering Dependencies via Algorithmic Mutual Information: A Case Study in DNA Sequence Comparisons ↗Aleksandar Milosavljević19 citations
34. Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition ↗Arie Ben‐David, Janice Mandel18 citations
35. An Integration of Rule Induction and Exemplar-Based Learning for Graded Concepts ↗Jianping Zhang, Ryszard S. Michalski15 citations
36. Learning binary relations using weighted majority voting ↗Sally A. Goldman, Manfred K. Warmuth15 citations
37. DEXTER: A System that Experiments with Choices of Training Data Using Expert Knowledge in the Domain of DNA Hydration ↗Dawn Cohen, Casimir A. Kulikowski, Helen Miriam Berman14 citations
38. A Branch and Bound Incremental Conceptual Clusterer ↗Arthur J. Nevins13 citations
39. On the Stochastic Complexity of Learning Realizable and Unrealizable Rules ↗Ronny Meir, Neri Merhav13 citations
40. Probably Almost Discriminative Learning ↗Kenji Yamanishi12 citations
41. Learning from a population of hypotheses ↗Michael J. Kearns, H. Sebastian Seung8 citations
42. On the complexity of function learning ↗Peter L. Auer, Philip M. Long, Wolfgang Maass et al.8 citations
43. Bounding the Vapnik-Chervonenkis Dimension of Concept Classes Parameterized by Real Numbers ↗Paul W. Goldberg, Mark Jerrum7 citations
44. Technical Note: Bias and the Quantification of Stability ↗Peter D. Turney7 citations
45. Piecemeal Learning of an Unknown Environment ↗Margrit Betke, Ronald L. Rivest, Mona Singh6 citations
46. Probably almost discriminative learning ↗Kenji Yamanishi6 citations
47. Comprehension Grammars Generated from Machine Learning of Natural Languages ↗Patrick Suppes, Michael Böttner, Lin Liang5 citations
48. Use of Adaptive Networks to Define Highly Predictable Protein Secondary–Structure Classes ↗Alan S. Lapedes, Evan W. Steeg, Robert M. Farber3 citations
49. A Reply to Towell's Book Review of Neural Network Perception for Mobile Robot Guidance ↗Dean Pomerleau2 citations
50. Introduction ↗JUDE W. SHAVLIK, Lawrence Hunter, David B. Searls2 citations
51. Searching for Representations to Improve Protein Sequence Fold-Class Prediction ↗Thomas R. Ioerger, Larry A. Rendell, Shankar Subramaniam2 citations
52. Shifting Vocabulary Bias in Speedup Learning ↗Devika Subramanian2 citations
53. Introduction ↗JUDE W. SHAVLIK, Lawrence Hunter, David B. Searls1 citation
54. Learning from a Population of Hypotheses ↗Michael J. Kearns, H. Sebastian Seung1 citation
55. Book Review: Neural Network Perception For Mobile Robot Guidance by Dean A. Pomerleau. Kluwer Academic Publishers, 1993 ↗Geoffrey G. Towell
56. Guest Editor's Introduction ↗Sally A. Goldman
57. Guest editor's introduction ↗Sally A. Goldman
58. Libro verde del control y fiscalización ambiental en la cuenca del río Huasco. ↗Serplac Iii Región Atacama, Cooperación Alemana, Chile. Ministerio de Bienes Nacionales
59. Neural network perception for mobile robot guidance by Dean A. Pomerleau. Kluwer Academic Publishers, 1993 ↗Geoffrey G. Towell
60. On the Complexity of Function Learning ↗Peter L. Auer, Philip M. Long, Wolfgang Maass et al.

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