---
title: "ICML 2005 — all accepted papers with summaries and citations"
description: "All 140 papers of ICML 2005 · page 1 of 2, the most cited first; those with our summary link to it."
canonical: "https://research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2005/papers/"
---
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# ICML 2005: all accepted papers

140 papers · page 1 of 2 · the most cited first · [← ICML 2005](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2005/)

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1. **[Learning to rank using gradient descent](https://md.research.elamur.ai/free/en/papers/burges-2005-learning-rank-using-gradient/)**Chris J. C. Burges, Tal Shaked, Erin Renshaw et al.*2,757 citations · our summary*
2. **[Predicting good probabilities with supervised learning ↗](https://doi.org/10.1145/1102351.1102430)**Alexandru Niculescu-Mizil, Rich Caruana*1,766 citations*
3. **[Fast maximum margin matrix factorization for collaborative prediction ↗](https://doi.org/10.1145/1102351.1102441)**Jasson D. M. Rennie, Nathan Srebro*939 citations*
4. **[A support vector method for multivariate performance measures ↗](https://doi.org/10.1145/1102351.1102399)**Thorsten Joachims*786 citations*
5. **[Comparing clusterings ↗](https://doi.org/10.1145/1102351.1102424)**Marina Meilă*589 citations*
6. **[Non-negative tensor factorization with applications to statistics and computer vision ↗](https://doi.org/10.1145/1102351.1102451)**Amnon Shashua, Tamir Hazan*490 citations*
7. **[Near-optimal sensor placements in Gaussian processes ↗](https://doi.org/10.1145/1102351.1102385)**Carlos Guestrin, Andreas Krause, Ajit Paul Singh*454 citations*
8. **[Learning structured prediction models ↗](https://doi.org/10.1145/1102351.1102464)**Ben Taskar, Vassil Chatalbashev, Daphne Koller et al.*444 citations*
9. **[Beyond the point cloud ↗](https://doi.org/10.1145/1102351.1102455)**Vikas Sindhwani, Partha Niyogi, Mikhail Belkin*439 citations*
10. **[Learning from labeled and unlabeled data on a directed graph ↗](https://doi.org/10.1145/1102351.1102482)**Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf*403 citations*
11. **[High speed obstacle avoidance using monocular vision and reinforcement learning ↗](https://doi.org/10.1145/1102351.1102426)**Jeff Michels, Ashutosh Saxena, Andrew Ng*394 citations*
12. **[Learning Gaussian processes from multiple tasks ↗](https://doi.org/10.1145/1102351.1102479)**Kai Yu, Volker Tresp, Anton Schwaighofer*380 citations*
13. **[Preference learning with Gaussian processes ↗](https://doi.org/10.1145/1102351.1102369)**Wei Chu, Zoubin Ghahramani*361 citations*
14. **[Bayesian hierarchical clustering ↗](https://doi.org/10.1145/1102351.1102389)**Katherine Heller, Zoubin Ghahramani*357 citations*
15. **[Reinforcement learning with Gaussian processes ↗](https://doi.org/10.1145/1102351.1102377)**Yaakov Engel, Shie Mannor, Ron Meir*335 citations*
16. **[The cross entropy method for classification ↗](https://doi.org/10.1145/1102351.1102422)**Shie Mannor, Dori Peleg A, Reuven Y. Rubinstein*312 citations*
17. **[Naive Bayes models for probability estimation ↗](https://doi.org/10.1145/1102351.1102418)**Daniel Lowd, Pedro Domingos*304 citations*
18. **[Learning the structure of Markov logic networks ↗](https://doi.org/10.1145/1102351.1102407)**Stanley Kok, Pedro Domingos*298 citations*
19. **[Modeling word burstiness using the Dirichlet distribution ↗](https://doi.org/10.1145/1102351.1102420)**Rasmus Elsborg Madsen, David Kauchak, Charles Elkan*280 citations*
20. **[New approaches to support vector ordinal regression ↗](https://doi.org/10.1145/1102351.1102370)**Wei Chu, S. Sathiya Keerthi*277 citations*
21. **[Using additive expert ensembles to cope with concept drift ↗](https://doi.org/10.1145/1102351.1102408)**J. Zico Kolter, Marcus A. Maloof*261 citations*
22. **[Identifying useful subgoals in reinforcement learning by local graph partitioning ↗](https://doi.org/10.1145/1102351.1102454)**Özgür Şimşek, Alicia P. Wolfe, Andrew G. Barto*238 citations*
23. **[Predictive low-rank decomposition for kernel methods ↗](https://doi.org/10.1145/1102351.1102356)**Francis Bach, Michael I. Jordan*238 citations*
24. **[Exploration and apprenticeship learning in reinforcement learning ↗](https://doi.org/10.1145/1102351.1102352)**Pieter Abbeel, Andrew Ng*224 citations*
25. **[Supervised versus multiple instance learning ↗](https://doi.org/10.1145/1102351.1102439)**Soumya Ray, Mark W. Craven*222 citations*
26. **[Supervised clustering with support vector machines ↗](https://doi.org/10.1145/1102351.1102379)**Thomas Finley, Thorsten Joachims*212 citations*
27. **[Logistic regression with an auxiliary data source ↗](https://doi.org/10.1145/1102351.1102415)**Xuejun Liao, Ya Xue, Lawrence Carin*203 citations*
28. **[Intrinsic dimensionality estimation of submanifolds in R d ↗](https://doi.org/10.1145/1102351.1102388)**Matthias Hein, Jean-Yves Audibert*185 citations*
29. **[Integer linear programming inference for conditional random fields ↗](https://doi.org/10.1145/1102351.1102444)**Dan Roth, Wen-tau Yih*179 citations*
30. **[Heteroscedastic Gaussian process regression ↗](https://doi.org/10.1145/1102351.1102413)**Quoc Viet Le, Alex J. Smola, Stéphane Canu*175 citations*
31. **[Semi-supervised graph clustering ↗](https://doi.org/10.1145/1102351.1102409)**Brian Kulis, Sugato Basu, Inderjit S. Dhillon et al.*174 citations*
32. **[Harmonic mixtures ↗](https://doi.org/10.1145/1102351.1102484)**Xiaojin Zhu, John Lafferty*170 citations*
33. **[Learning as search optimization ↗](https://doi.org/10.1145/1102351.1102373)**Hal Daumé, Daniel Marcu*157 citations*
34. **[Optimal assignment kernels for attributed molecular graphs ↗](https://doi.org/10.1145/1102351.1102380)**Holger Fröhlich, Jörg K. Wegner, Florian Sieker et al.*145 citations*
35. **[Fast condensed nearest neighbor rule ↗](https://doi.org/10.1145/1102351.1102355)**Fabrizio Angiulli*144 citations*
36. **[A theoretical analysis of Model-Based Interval Estimation ↗](https://doi.org/10.1145/1102351.1102459)**Alexander L. Strehl, Michael L. Littman*135 citations*
37. **[Dynamic preferences in multi-criteria reinforcement learning ↗](https://doi.org/10.1145/1102351.1102427)**Sriraam Natarajan, Prasad V. Tadepalli*132 citations*
38. **[Bounded real-time dynamic programming ↗](https://doi.org/10.1145/1102351.1102423)**H. Brendan McMahan, Maxim A. Likhachev, Geoffrey J. Gordon*128 citations*
39. **[2D Conditional Random Fields for Web information extraction ↗](https://doi.org/10.1145/1102351.1102483)**Jun Zhu, Zaiqing Nie, Ji-Rong Wen et al.*124 citations*
40. **[Bayesian sparse sampling for on-line reward optimization ↗](https://doi.org/10.1145/1102351.1102472)**Tao Wang, Daniel J. Lizotte, Michael Bowling et al.*114 citations*
41. **[Multi-way distributional clustering via pairwise interactions ↗](https://doi.org/10.1145/1102351.1102357)**Ron Bekkerman, Ran El‐Yaniv, Andrew McCallum*105 citations*
42. **[Analysis and extension of spectral methods for nonlinear dimensionality reduction ↗](https://doi.org/10.1145/1102351.1102450)**Fei Sha, Lawrence K. Saul*104 citations*
43. **[Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM ↗](https://doi.org/10.1145/1102351.1102365)**Sylvain Calinon, Aude Billard*103 citations*
44. **[Proto-value functions ↗](https://doi.org/10.1145/1102351.1102421)**Sridhar Mahadevan*94 citations*
45. **[Online learning over graphs ↗](https://doi.org/10.1145/1102351.1102390)**Mark Herbster, Massimiliano Pontil, L. J. Wainer*93 citations*
46. **[Healing the relevance vector machine through augmentation ↗](https://doi.org/10.1145/1102351.1102438)**Carl Edward Rasmussen, Joaquin Quiñonero-Candela*90 citations*
47. **[Learning hierarchical multi-category text classification models ↗](https://doi.org/10.1145/1102351.1102445)**Juho Rousu, Craig J. Saunders, Sándor Szedmák et al.*90 citations*
48. **[Multi-instance tree learning ↗](https://doi.org/10.1145/1102351.1102359)**Hendrik Blockeel, David Page, Ashwin Srinivasan*90 citations*
49. **[A general regression technique for learning transductions ↗](https://doi.org/10.1145/1102351.1102371)**Corinna Cortes, Mehryar Mohri, Jason Weston*86 citations*
50. **[Hierarchic Bayesian models for kernel learning ↗](https://doi.org/10.1145/1102351.1102382)**Mark Girolami, Simon Rogers*78 citations*
51. **[Learning predictive state representations in dynamical systems without reset ↗](https://doi.org/10.1145/1102351.1102475)**Britton Wolfe, Michael R. James, Satinder Pal Singh*76 citations*
52. **[Statistical and computational analysis of locality preserving projection ↗](https://doi.org/10.1145/1102351.1102387)**Xiaofei He, Deng Cai, Wanli Min*72 citations*
53. **[A martingale framework for concept change detection in time-varying data streams ↗](https://doi.org/10.1145/1102351.1102392)**Shen-Shyang Ho*68 citations*
54. **[Discriminative versus generative parameter and structure learning of Bayesian network classifiers ↗](https://doi.org/10.1145/1102351.1102434)**Franz Pernkopf, Jeff Bilmes*67 citations*
55. **[ROC confidence bands ↗](https://doi.org/10.1145/1102351.1102419)**Sofus A. Macskassy, Foster John Provost, Saharon Rosset*66 citations*
56. **[A brain computer interface with online feedback based on magnetoencephalography ↗](https://doi.org/10.1145/1102351.1102410)**Thomas Navin Lal, Niels Birbaumer, Bernhard Schölkopf et al.*65 citations*
57. **[Weighted decomposition kernels ↗](https://doi.org/10.1145/1102351.1102425)**Sauro Menchetti, Fabrizio Costa, Paolo Frasconi*65 citations*
58. **[An efficient method for simplifying support vector machines ↗](https://doi.org/10.1145/1102351.1102429)**Duc-Dung Nguyen, Tu-Bao Ho*63 citations*
59. **[Incomplete-data classification using logistic regression ↗](https://doi.org/10.1145/1102351.1102474)**David P. Williams, Xuejun Liao, Ya Xue et al.*63 citations*
60. **[Clustering through ranking on manifolds ↗](https://doi.org/10.1145/1102351.1102361)**Markus Breitenbach, Gregory Z. Grudić*59 citations*
61. **[Error limiting reductions between classification tasks ↗](https://doi.org/10.1145/1102351.1102358)**Alina Beygelzimer, Varsha Dani, Tom Hayes et al.*59 citations*
62. **[Predicting relative performance of classifiers from samples ↗](https://doi.org/10.1145/1102351.1102414)**Rui Leite, Pavel Brazdil*59 citations*
63. **[Finite time bounds for sampling based fitted value iteration ↗](https://doi.org/10.1145/1102351.1102462)**Csaba Szepesvári, Rémi Munos*58 citations*
64. **[Q-learning of sequential attention for visual object recognition from informative local descriptors ↗](https://doi.org/10.1145/1102351.1102433)**Lucas Paletta, Gerald Fritz, Christin Seifert*58 citations*
65. **[A new Mallows distance based metric for comparing clusterings ↗](https://doi.org/10.1145/1102351.1102481)**Ding Xuan Zhou, Jia Li, Hongyuan Zha*57 citations*
66. **[Relating reinforcement learning performance to classification performance ↗](https://doi.org/10.1145/1102351.1102411)**John C. Langford, Bianca Zadrozny*55 citations*
67. **[Optimizing abstaining classifiers using ROC analysis ↗](https://doi.org/10.1145/1102351.1102435)**Tadeusz Pietraszek*54 citations*
68. **[Action respecting embedding ↗](https://doi.org/10.1145/1102351.1102360)**Michael Bowling, Ali Ghodsi, Dana F. Wilkinson*53 citations*
69. **[Active learning for Hidden Markov Models ↗](https://doi.org/10.1145/1102351.1102353)**Brigham S. Anderson, Andrew Moore*53 citations*
70. **[Evaluating machine learning for information extraction ↗](https://doi.org/10.1145/1102351.1102395)**Neil Ireson, Fabio Ciravegna, Mary Elaine Califf et al.*53 citations*
71. **[Robust one-class clustering using hybrid global and local search ↗](https://doi.org/10.1145/1102351.1102386)**Gunjan Gupta, Joydeep Ghosh*50 citations*
72. **[Large scale genomic sequence SVM classifiers ↗](https://doi.org/10.1145/1102351.1102458)**Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf*47 citations*
73. **[Linear Asymmetric Classifier for cascade detectors ↗](https://doi.org/10.1145/1102351.1102476)**Jianxin Wu, Matthew D. Mullin, James Matthew Rehg*47 citations*
74. **[Building Sparse Large Margin Classifiers ↗](https://doi.org/10.1145/1102351.1102477)**Mingrui Wu, Bernhard Schölkopf, Gökhan Bakır*46 citations*
75. **[Core Vector Regression for very large regression problems ↗](https://doi.org/10.1145/1102351.1102466)**Ivor Wai-Hung Tsang, James Tin-Yau Kwok, Kimo T. Lai*46 citations*
76. **[Multimodal oriented discriminant analysis ↗](https://doi.org/10.1145/1102351.1102374)**Fernando De la Torre, Takeo Kanade A*46 citations*
77. **[Online feature selection for pixel classification ↗](https://doi.org/10.1145/1102351.1102383)**Karen A. Glocer, Damian R. Eads, James P. Theiler*45 citations*
78. **[Learning to compete, compromise, and cooperate in repeated general-sum games ↗](https://doi.org/10.1145/1102351.1102372)**Jacob W. Crandall, Michael A. Goodrich*42 citations*
79. **[A causal approach to hierarchical decomposition of factored MDPs ↗](https://doi.org/10.1145/1102351.1102402)**Anders Jönsson, Andrew G. Barto*41 citations*
80. **[Expectation maximization algorithms for conditional likelihoods ↗](https://doi.org/10.1145/1102351.1102446)**Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski*37 citations*
81. **[Learning approximate preconditions for methods in hierarchical plans ↗](https://doi.org/10.1145/1102351.1102394)**Okhtay Ilghami, Héctor Muñoz‐Avila, Dana S. Nau et al.*37 citations*
82. **[Multi-class protein fold recognition using adaptive codes ↗](https://doi.org/10.1145/1102351.1102393)**Eugene Ie, Jason Weston, William Stafford Noble et al.*36 citations*
83. **[Estimating and computing density based distance metrics ↗](https://doi.org/10.1145/1102351.1102447)**Sajama, Alon Orlitsky*34 citations*
84. **[Predicting probability distributions for surf height using an ensemble of mixture density networks ↗](https://doi.org/10.1145/1102351.1102366)**Michael Carney, Pádraig Cunningham, Jim Dowling et al.*34 citations*
85. **[Supervised dimensionality reduction using mixture models ↗](https://doi.org/10.1145/1102351.1102448)**Sajama, Alon Orlitsky*33 citations*
86. **[Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes ↗](https://doi.org/10.1145/1102351.1102398)**Yushi Jing, Vladimir Pavlović, James Matthew Rehg*32 citations*
87. **[Independent subspace analysis using geodesic spanning trees ↗](https://doi.org/10.1145/1102351.1102436)**Barnabás Póczos, András Lörincz*32 citations*
88. **[Augmenting naive Bayes for ranking ↗](https://doi.org/10.1145/1102351.1102480)**Harry Zhang, Liangxiao Jiang, Jiang Su*30 citations*
89. **[Learning predictive representations from a history ↗](https://doi.org/10.1145/1102351.1102473)**Eric Wiewiora*30 citations*
90. **[Compact approximations to Bayesian predictive distributions ↗](https://doi.org/10.1145/1102351.1102457)**Edward Snelson, Zoubin Ghahramani*28 citations*
91. **[Error bounds for correlation clustering ↗](https://doi.org/10.1145/1102351.1102400)**Thorsten Joachims, John E. Hopcroft*28 citations*
92. **[Learning discontinuities with products-of-sigmoids for switching between local models ↗](https://doi.org/10.1145/1102351.1102465)**Marc Toussaint, Sethu Vijayakumar*27 citations*
93. **[Learning first-order probabilistic models with combining rules ↗](https://doi.org/10.1145/1102351.1102428)**Sriraam Natarajan, Prasad V. Tadepalli, Eric E. Altendorf et al.*27 citations*
94. **[Object correspondence as a machine learning problem ↗](https://doi.org/10.1145/1102351.1102449)**Bernhard Schölkopf, Florian Steinke, Volker Blanz*27 citations*
95. **[Propagating distributions on a hypergraph by dual information regularization ↗](https://doi.org/10.1145/1102351.1102467)**Koji Tsuda*25 citations*
96. **[Hierarchical Dirichlet model for document classification ↗](https://doi.org/10.1145/1102351.1102468)**Sriharsha Veeramachaneni, Diego Sona, Paolo Avesani*23 citations*
97. **[Learn to weight terms in information retrieval using category information ↗](https://doi.org/10.1145/1102351.1102396)**Rong Jin, Joyce Yue Chai, Luo Si*23 citations*
98. **[Combining model-based and instance-based learning for first order regression ↗](https://doi.org/10.1145/1102351.1102376)**Kurt Driessens, Sašo Džeroski*22 citations*
99. **[Fast inference and learning in large-state-space HMMs ↗](https://doi.org/10.1145/1102351.1102452)**Sajid M. Siddiqi, Andrew Moore*22 citations*
100. **[Unifying the error-correcting and output-code AdaBoost within the margin framework ↗](https://doi.org/10.1145/1102351.1102461)**Yijun Sun, Siniša Todorović, Jian Li et al.*22 citations*

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