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ICML 2005 — accepted papers

ICML 2005 is the 2005 edition of the International Conference on Machine Learning (ICML). OpenAlex lists 140 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

 140papers in the proceedings 1work in our library 2,906citations of these works

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

  1. Learning to rank using gradient descentChris J. C. Burges, Tal Shaked, Erin Renshaw et al.2,757 citations · our summary
  2. Predicting good probabilities with supervised learning ↗Alexandru Niculescu-Mizil, Rich Caruana1,766 citations
  3. Fast maximum margin matrix factorization for collaborative prediction ↗Jasson D. M. Rennie, Nathan Srebro939 citations
  4. A support vector method for multivariate performance measures ↗Thorsten Joachims786 citations
  5. Comparing clusterings ↗Marina Meilă589 citations
  6. Non-negative tensor factorization with applications to statistics and computer vision ↗Amnon Shashua, Tamir Hazan490 citations
  7. Near-optimal sensor placements in Gaussian processes ↗Carlos Guestrin, Andreas Krause, Ajit Paul Singh454 citations
  8. Learning structured prediction models ↗Ben Taskar, Vassil Chatalbashev, Daphne Koller et al.444 citations
  9. Beyond the point cloud ↗Vikas Sindhwani, Partha Niyogi, Mikhail Belkin439 citations
  10. Learning from labeled and unlabeled data on a directed graph ↗Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf403 citations

All accepted papers (140)

The most cited first; 1 with our summary link to their page here, the others to the original.

  1. Learning to rank using gradient descentChris J. C. Burges, Tal Shaked, Erin Renshaw et al.2,757 citations · our summary
  2. Predicting good probabilities with supervised learning ↗Alexandru Niculescu-Mizil, Rich Caruana1,766 citations
  3. Fast maximum margin matrix factorization for collaborative prediction ↗Jasson D. M. Rennie, Nathan Srebro939 citations
  4. A support vector method for multivariate performance measures ↗Thorsten Joachims786 citations
  5. Comparing clusterings ↗Marina Meilă589 citations
  6. Non-negative tensor factorization with applications to statistics and computer vision ↗Amnon Shashua, Tamir Hazan490 citations
  7. Near-optimal sensor placements in Gaussian processes ↗Carlos Guestrin, Andreas Krause, Ajit Paul Singh454 citations
  8. Learning structured prediction models ↗Ben Taskar, Vassil Chatalbashev, Daphne Koller et al.444 citations
  9. Beyond the point cloud ↗Vikas Sindhwani, Partha Niyogi, Mikhail Belkin439 citations
  10. Learning from labeled and unlabeled data on a directed graph ↗Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf403 citations
  11. High speed obstacle avoidance using monocular vision and reinforcement learning ↗Jeff Michels, Ashutosh Saxena, Andrew Ng394 citations
  12. Learning Gaussian processes from multiple tasks ↗Kai Yu, Volker Tresp, Anton Schwaighofer380 citations
  13. Preference learning with Gaussian processes ↗Wei Chu, Zoubin Ghahramani361 citations
  14. Bayesian hierarchical clustering ↗Katherine Heller, Zoubin Ghahramani357 citations
  15. Reinforcement learning with Gaussian processes ↗Yaakov Engel, Shie Mannor, Ron Meir335 citations
  16. The cross entropy method for classification ↗Shie Mannor, Dori Peleg A, Reuven Y. Rubinstein312 citations
  17. Naive Bayes models for probability estimation ↗Daniel Lowd, Pedro Domingos304 citations
  18. Learning the structure of Markov logic networks ↗Stanley Kok, Pedro Domingos298 citations
  19. Modeling word burstiness using the Dirichlet distribution ↗Rasmus Elsborg Madsen, David Kauchak, Charles Elkan280 citations
  20. New approaches to support vector ordinal regression ↗Wei Chu, S. Sathiya Keerthi277 citations
  21. Using additive expert ensembles to cope with concept drift ↗J. Zico Kolter, Marcus A. Maloof261 citations
  22. Identifying useful subgoals in reinforcement learning by local graph partitioning ↗Özgür Şimşek, Alicia P. Wolfe, Andrew G. Barto238 citations
  23. Predictive low-rank decomposition for kernel methods ↗Francis Bach, Michael I. Jordan238 citations
  24. Exploration and apprenticeship learning in reinforcement learning ↗Pieter Abbeel, Andrew Ng224 citations
  25. Supervised versus multiple instance learning ↗Soumya Ray, Mark W. Craven222 citations

See all 140 papers in ICML 2005 — accepted papers →

 Papers with our summary in our library (1)

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

  1. Learning to Rank using Gradient DescentInternational Conference on Machine Learning (ICML)Chris Burges, Tal Shaked, Erin Renshaw, et al.2005 · 2,906 citations

 Top topics

Topics of its works in our library, with the number of works on each.

Information retrieval & search (1)

 Fields

Computer Science (1)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🧑‍🔬Erin Renshaw1 work here · 2,906 citations

 Top institutions

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

🏢MicrosoftRedmond · United States1 work here

works and citations from OpenAlex and our library.

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