📰 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.

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 ↗Leo Breiman17,218 citations
2. Bagging predictorsLeo Breiman16,310 citations · our summary
3. Stacked Regressions ↗Leo Breiman1,912 citations
4. Learning in the Presence of Concept Drift and Hidden Contexts ↗Gerhard Widmer, Miroslav Kubát1,840 citations
5. Linear Least-Squares algorithms for temporal difference learning ↗Steven J. Bradtke, Andrew G. Barto599 citations
6. Reinforcement learning with replacing eligibility traces ↗Satinder Pal Singh, Richard S. Sutton575 citations
7. Feature-based methods for large scale dynamic programming ↗John N. Tsitsiklis, Benjamin Van Roy432 citations
8. Average reward reinforcement learning: Foundations, algorithms, and empirical results ↗Sridhar Mahadevan385 citations
9. Efficient reinforcement learning through symbiotic evolution ↗David E. Moriarty, Risto P Miikkulainen325 citations
10. A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval ↗Claudio Carpineto, Giovanni Romano309 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 ↗Leo Breiman17,218 citations
2. Bagging predictorsLeo Breiman16,310 citations · our summary
3. Stacked Regressions ↗Leo Breiman1,912 citations
4. Learning in the Presence of Concept Drift and Hidden Contexts ↗Gerhard Widmer, Miroslav Kubát1,840 citations
5. Linear Least-Squares algorithms for temporal difference learning ↗Steven J. Bradtke, Andrew G. Barto599 citations
6. Reinforcement learning with replacing eligibility traces ↗Satinder Pal Singh, Richard S. Sutton575 citations
7. Feature-based methods for large scale dynamic programming ↗John N. Tsitsiklis, Benjamin Van Roy432 citations
8. Average reward reinforcement learning: Foundations, algorithms, and empirical results ↗Sridhar Mahadevan385 citations
9. Efficient reinforcement learning through symbiotic evolution ↗David E. Moriarty, Risto P Miikkulainen325 citations
10. A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval ↗Claudio Carpineto, Giovanni Romano309 citations
11. Incremental multi-step Q-learning ↗Jing Peng, Ronald J. Williams286 citations
12. Purposive behavior acquisition for a real robot by vision-based reinforcement learning ↗Minoru Asada, Shoichi Noda, Sukoya Tawaratsumida et al.274 citations
13. Technical Note: Some Properties of Splitting Criteria ↗Leo Breiman270 citations
14. Unifying Instance-Based and Rule-Based Induction ↗Pedro Domingos242 citations
15. The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length ↗Dana Ron, Yoram Singer, Naftali Tishby185 citations
16. Error reduction through learning multiple descriptions ↗Kamal Ali, Michael J. Pazzani163 citations
17. Exploration Bonuses and Dual Control ↗Peter Dayan, Terrence J. Sejnowski118 citations
18. The effect of representation and knowledge on goal-directed exploration with reinforcement-learning algorithms ↗Sven Koenig, Reid G. Simmons102 citations
19. Creating advice-taking reinforcement learners ↗Richard Maclin, JUDE W. SHAVLIK98 citations
20. Representation of Finite State Automata in Recurrent Radial Basis Function Networks ↗Paolo Frasconi, Marco Gori, Marco Maggini et al.97 citations
21. Robot programming by Demonstration (RPD): Supporting the induction by human interaction ↗H. Friedrich, S. M�nch, Rüdiger Dillmann et al.77 citations
22. On-line Prediction and Conversion Strategies ↗Nicolò Cesa‐Bianchi, Yoav Freund, David P. Helmbold et al.72 citations
23. Scaling Up Inductive Learning with Massive Parallelism ↗Foster John Provost, John M. Aronis56 citations
24. Active learning for vision-based robot grasping ↗Marcos Salganicoff, Lyle Ungar, Ruzena Bajcsy51 citations
25. BEXA: A Covering Algorithm for Learning Propositional Concept Descriptions ↗H Theron, Ian Cloete44 citations

See all 83 papers in Machine Learning 1996 — papers →

📄 Works with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. Bagging PredictorsLeo Breiman1996 · 16,517 citations

📚 Fields

🖥️Computer Science (1)➗Mathematics (1)

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓University of California, BerkeleyBerkeley · United States1 work here

works and citations from OpenAlex and our library.

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