--- title: "Machine Learning 1996 — papers — Elamur Research" description: "Machine Learning 1996 — papers: 1 paper in the Elamur Research library, with our summaries, ranked by citations." canonical: "https://research.elamur.ai/free/en/venues/machine-learning/1996/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/machine-learning/1996/) [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/) / 1996 # Machine Learning 1996 — papers The works of Machine Learning published in 1996 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. [**83** works that year](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/machine-learning/1996/#works) · [**16,517** citations of these works](https://md.research.elamur.ai/free/en/venues/machine-learning/1996/#works) ## Most cited papers By their OpenAlex citations; a paper with our summary links to its page here, the others to the original. 1. **[Bagging Predictors ↗](https://doi.org/10.1023/a:1018054314350)**Leo Breiman*17,218 citations* 2. **[Bagging predictors](https://md.research.elamur.ai/free/en/papers/breiman-1996-bagging-predictors/)**Leo Breiman*16,310 citations · our summary* 3. **[Stacked Regressions ↗](https://doi.org/10.1007/bf00117832)**Leo Breiman*1,912 citations* 4. **[Learning in the Presence of Concept Drift and Hidden Contexts ↗](https://doi.org/10.1007/bf00116900)**Gerhard Widmer, Miroslav Kubát*1,840 citations* 5. **[Linear Least-Squares algorithms for temporal difference learning ↗](https://doi.org/10.1007/bf00114723)**Steven J. Bradtke, Andrew G. Barto*599 citations* 6. **[Reinforcement learning with replacing eligibility traces ↗](https://doi.org/10.1007/bf00114726)**Satinder Pal Singh, Richard S. Sutton*575 citations* 7. **[Feature-based methods for large scale dynamic programming ↗](https://doi.org/10.1007/bf00114724)**John N. Tsitsiklis, Benjamin Van Roy*432 citations* 8. **[Average reward reinforcement learning: Foundations, algorithms, and empirical results ↗](https://doi.org/10.1007/bf00114727)**Sridhar Mahadevan*385 citations* 9. **[Efficient reinforcement learning through symbiotic evolution ↗](https://doi.org/10.1007/bf00114722)**David E. Moriarty, Risto P Miikkulainen*325 citations* 10. **[A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval ↗](https://doi.org/10.1007/bf00058654)**Claudio Carpineto, Giovanni Romano*309 citations* ## All works of the year (83) The most cited first; 1 with our summary link to their page here, the others to the original. 1. **[Bagging Predictors ↗](https://doi.org/10.1023/a:1018054314350)**Leo Breiman*17,218 citations* 2. **[Bagging predictors](https://md.research.elamur.ai/free/en/papers/breiman-1996-bagging-predictors/)**Leo Breiman*16,310 citations · our summary* 3. **[Stacked Regressions ↗](https://doi.org/10.1007/bf00117832)**Leo Breiman*1,912 citations* 4. **[Learning in the Presence of Concept Drift and Hidden Contexts ↗](https://doi.org/10.1007/bf00116900)**Gerhard Widmer, Miroslav Kubát*1,840 citations* 5. **[Linear Least-Squares algorithms for temporal difference learning ↗](https://doi.org/10.1007/bf00114723)**Steven J. Bradtke, Andrew G. Barto*599 citations* 6. **[Reinforcement learning with replacing eligibility traces ↗](https://doi.org/10.1007/bf00114726)**Satinder Pal Singh, Richard S. Sutton*575 citations* 7. **[Feature-based methods for large scale dynamic programming ↗](https://doi.org/10.1007/bf00114724)**John N. Tsitsiklis, Benjamin Van Roy*432 citations* 8. **[Average reward reinforcement learning: Foundations, algorithms, and empirical results ↗](https://doi.org/10.1007/bf00114727)**Sridhar Mahadevan*385 citations* 9. **[Efficient reinforcement learning through symbiotic evolution ↗](https://doi.org/10.1007/bf00114722)**David E. Moriarty, Risto P Miikkulainen*325 citations* 10. **[A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval ↗](https://doi.org/10.1007/bf00058654)**Claudio Carpineto, Giovanni Romano*309 citations* 11. **[Incremental multi-step Q-learning ↗](https://doi.org/10.1007/bf00114731)**Jing Peng, Ronald J. Williams*286 citations* 12. **[Purposive behavior acquisition for a real robot by vision-based reinforcement learning ↗](https://doi.org/10.1007/bf00117447)**Minoru Asada, Shoichi Noda, Sukoya Tawaratsumida et al.*274 citations* 13. **[Technical Note: Some Properties of Splitting Criteria ↗](https://doi.org/10.1007/bf00117831)**Leo Breiman*270 citations* 14. **[Unifying Instance-Based and Rule-Based Induction ↗](https://doi.org/10.1007/bf00058656)**Pedro Domingos*242 citations* 15. **[The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length ↗](https://doi.org/10.1023/a:1026490906255)**Dana Ron, Yoram Singer, Naftali Tishby*185 citations* 16. **[Error reduction through learning multiple descriptions ↗](https://doi.org/10.1007/bf00058611)**Kamal Ali, Michael J. Pazzani*163 citations* 17. **[Exploration Bonuses and Dual Control ↗](https://doi.org/10.1007/bf00115298)**Peter Dayan, Terrence J. Sejnowski*118 citations* 18. **[The effect of representation and knowledge on goal-directed exploration with reinforcement-learning algorithms ↗](https://doi.org/10.1007/bf00114729)**Sven Koenig, Reid G. Simmons*102 citations* 19. **[Creating advice-taking reinforcement learners ↗](https://doi.org/10.1007/bf00114730)**Richard Maclin, JUDE W. SHAVLIK*98 citations* 20. **[Representation of Finite State Automata in Recurrent Radial Basis Function Networks ↗](https://doi.org/10.1007/bf00116897)**Paolo Frasconi, Marco Gori, Marco Maggini et al.*97 citations* 21. **[Robot programming by Demonstration (RPD): Supporting the induction by human interaction ↗](https://doi.org/10.1007/bf00117443)**H. Friedrich, S. M�nch, Rüdiger Dillmann et al.*77 citations* 22. **[On-line Prediction and Conversion Strategies ↗](https://doi.org/10.1007/bf00115301)**Nicolò Cesa‐Bianchi, Yoav Freund, David P. Helmbold et al.*72 citations* 23. **[Scaling Up Inductive Learning with Massive Parallelism ↗](https://doi.org/10.1007/bf00116898)**Foster John Provost, John M. Aronis*56 citations* 24. **[Active learning for vision-based robot grasping ↗](https://doi.org/10.1007/bf00117446)**Marcos Salganicoff, Lyle Ungar, Ruzena Bajcsy*51 citations* 25. **[BEXA: A Covering Algorithm for Learning Propositional Concept Descriptions ↗](https://doi.org/10.1007/bf00117830)**H Theron, Ian Cloete*44 citations* [See all 83 papers in Machine Learning 1996 — papers →](https://md.research.elamur.ai/free/en/venues/machine-learning/1996/papers/) ## Works with our summary in our library (1) The most cited first (OpenAlex citations plus our library's). 1. [**Bagging Predictors**Leo Breiman*1996 · 16,517 citations*](https://md.research.elamur.ai/free/en/papers/breiman-1996-bagging-predictors/) ## Fields [Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Mathematics (1)](https://md.research.elamur.ai/free/en/shelves/mathematics/) ## Top institutions Institutions on the bylines of its works here, by the number of works. [🎓**University of California, Berkeley** Berkeley · United States 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-california-berkeley/) works and citations from OpenAlex and our library. - [← previous Machine Learning 1995](https://md.research.elamur.ai/free/en/venues/machine-learning/1995/) - [next → Machine Learning 2000](https://md.research.elamur.ai/free/en/venues/machine-learning/2000/) - [↑ back to Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)