--- title: "Machine Learning 1995 — papers — Elamur Research" description: "Machine Learning 1995 — papers: 1 paper in the Elamur Research library, with our summaries, ranked by citations." canonical: "https://research.elamur.ai/free/en/venues/machine-learning/1995/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/machine-learning/1995/) [home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/) / 1995 # Machine Learning 1995 — papers The works of Machine Learning published in 1995 that our library holds (publisher: Springer Science+Business Media): 1 work, listed below with the most cited first; each has a page with our summary, its key points and its references. [**60** works that year](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/machine-learning/1995/#works) · [**59,451** citations of these works](https://md.research.elamur.ai/free/en/venues/machine-learning/1995/#works) ## Most cited papers By their OpenAlex citations; a paper with our summary links to its page here, the others to the original. 1. **[Support-Vector Networks](https://md.research.elamur.ai/free/en/papers/cortes-1995-support-vector-networks/)**Corinna Cortes, Vladimir N. Vapnik*58,873 citations · our summary* 2. **[Learning Bayesian Networks: The Combination of Knowledge and Statistical Data ↗](https://doi.org/10.1023/a:1022623210503)**David E. Heckerman, Dan Geiger, David M. Chickering*3,231 citations* 3. **[Learning Bayesian networks: The combination of knowledge and statistical data ↗](https://doi.org/10.1007/bf00994016)**David E. Heckerman, Dan Geiger, David M. Chickering*2,017 citations* 4. **[Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization ↗](https://doi.org/10.1007/bf00993379)**Timothy L. Bailey, Charles Elkan*670 citations* 5. **[Multivariate Decision Trees ↗](https://doi.org/10.1007/bf00994660)**Carla E. Brodley, Paul E. Utgoff*447 citations* 6. **[The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces ↗](https://doi.org/10.1023/a:1022656217772)**Andrew Moore, Christopher G. Atkeson*259 citations* 7. **[Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension ↗](https://doi.org/10.1007/bf00993593)**Sally Floyd, Manfred K. Warmuth*256 citations* 8. **[An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms ↗](https://doi.org/10.1007/bf00994658)**Dietrich Wettschereck, Thomas G. Dietterich*239 citations* 9. **[Monotonicity Maintenance in Information-Theoretic Machine Learning Algorithms ↗](https://doi.org/10.1007/bf00994659)**Arie Ben‐David*164 citations* 10. **[Automated Refinement of First-Order Horn-Clause Domain Theories ↗](https://doi.org/10.1007/bf01007461)**Bradley L. Richards, Raymond J. Mooney*140 citations* ## All works of the year (60) The most cited first; 1 with our summary link to their page here, the others to the original. 1. **[Support-Vector Networks](https://md.research.elamur.ai/free/en/papers/cortes-1995-support-vector-networks/)**Corinna Cortes, Vladimir N. Vapnik*58,873 citations · our summary* 2. **[Learning Bayesian Networks: The Combination of Knowledge and Statistical Data ↗](https://doi.org/10.1023/a:1022623210503)**David E. Heckerman, Dan Geiger, David M. Chickering*3,231 citations* 3. **[Learning Bayesian networks: The combination of knowledge and statistical data ↗](https://doi.org/10.1007/bf00994016)**David E. Heckerman, Dan Geiger, David M. Chickering*2,017 citations* 4. **[Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization ↗](https://doi.org/10.1007/bf00993379)**Timothy L. Bailey, Charles Elkan*670 citations* 5. **[Multivariate Decision Trees ↗](https://doi.org/10.1007/bf00994660)**Carla E. Brodley, Paul E. Utgoff*447 citations* 6. **[The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces ↗](https://doi.org/10.1023/a:1022656217772)**Andrew Moore, Christopher G. Atkeson*259 citations* 7. **[Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension ↗](https://doi.org/10.1007/bf00993593)**Sally Floyd, Manfred K. Warmuth*256 citations* 8. **[An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms ↗](https://doi.org/10.1007/bf00994658)**Dietrich Wettschereck, Thomas G. Dietterich*239 citations* 9. **[Monotonicity Maintenance in Information-Theoretic Machine Learning Algorithms ↗](https://doi.org/10.1007/bf00994659)**Arie Ben‐David*164 citations* 10. **[Automated Refinement of First-Order Horn-Clause Domain Theories ↗](https://doi.org/10.1007/bf01007461)**Bradley L. Richards, Raymond J. Mooney*140 citations* 11. **[Evaluation and Selection of Biases in Machine Learning ↗](https://doi.org/10.1007/bf00993472)**Diana F. Gordon, Marie Ellen Desjardins*140 citations* 12. **[The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces ↗](https://doi.org/10.1007/bf00993591)**Andrew Moore, Christopher G. Atkeson*137 citations* 13. **[Recursive Automatic Bias Selection for Classifier Construction ↗](https://doi.org/10.1007/bf00993475)**Carla E. Brodley*126 citations* 14. **[Technical note: Bias and the quantification of stability ↗](https://doi.org/10.1007/bf00993473)**Peter D. Turney*121 citations* 15. **[Genetic Algorithms, Operators, and DNA Fragment Assembly ↗](https://doi.org/10.1007/bf00993377)**Rebecca J. Parsons, Stephanie Forrest, Christian Burks*110 citations* 16. **[Neural Networks for Full-Scale Protein Sequence Classification: Sequence Encoding with Singular Value Decomposition ↗](https://doi.org/10.1007/bf00993384)**Cathy H. Wu, Michael W. Berry, Sailaja Shivakumar et al.*99 citations* 17. **[Inductive Policy: The Pragmatics of Bias Selection ↗](https://doi.org/10.1007/bf00993474)**Foster John Provost, Bruce G. Buchanan*89 citations* 18. **[ALECSYS and the AutonoMouse: Learning to Control a Real Robot by Distributed Classifier Systems ↗](https://doi.org/10.1007/bf00996270)**Marco Dorigo*72 citations* 19. **[Bounding the Vapnik-Chervonenkis dimension of concept classes parameterized by real numbers ↗](https://doi.org/10.1007/bf00993408)**Paul W. Goldberg, Mark Jerrum*65 citations* 20. **[A Comparison of ID3 and Backpropagation for English Text-To-Speech Mapping ↗](https://doi.org/10.1023/a:1022822623726)**Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri*58 citations* 21. **[Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning ↗](https://doi.org/10.1023/a:1022874607797)**Thomas Dean, Dana Angluin A, Kenneth Basye et al.*52 citations* 22. **[On Polynomial-Time Learnability in the Limit of Strictly Deterministic Automata ↗](https://doi.org/10.1007/bf01007463)**Takashi Yokomori*42 citations* 23. **[Piecemeal learning of an unknown environment ↗](https://doi.org/10.1007/bf00993411)**Margrit Betke, Ronald L. Rivest, Mona Singh*41 citations* 24. **[Declarative Bias for Specific-to-General ILP Systems ↗](https://doi.org/10.1007/bf00993477)**Hilde Adé, Luc De Raedt, Maurice Bruynooghe*39 citations* 25. **[Encouraging Experimental Results on Learning CNF ↗](https://doi.org/10.1007/bf00994661)**Raymond J. Mooney*38 citations* [See all 60 papers in Machine Learning 1995 — papers →](https://md.research.elamur.ai/free/en/venues/machine-learning/1995/papers/) ## Works with our summary in our library (1) The most cited first (OpenAlex citations plus our library's). 1. **[Support-Vector Networks](https://md.research.elamur.ai/free/en/papers/cortes-1995-support-vector-networks/) [Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)**Corinna Cortes, Vladimir Vapnik*1995 · 59,451 citations* ## Fields [Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/) ## Top institutions Institutions on the bylines of its works here, by the number of works. [🏢**AT&T** Bedminster · United States 1 work here](https://md.research.elamur.ai/free/en/companies/at-t/) works and citations from OpenAlex and our library. - [← previous Machine Learning 1991](https://md.research.elamur.ai/free/en/venues/machine-learning/1991/) - [next → Machine Learning 1996](https://md.research.elamur.ai/free/en/venues/machine-learning/1996/) - [↑ back to Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)