ICML 2005: all accepted papers
- Learning to rank using gradient descentChris J. C. Burges, Tal Shaked, Erin Renshaw et al.2,757 citations · our summary
- Predicting good probabilities with supervised learning ↗Alexandru Niculescu-Mizil, Rich Caruana1,766 citations
- Fast maximum margin matrix factorization for collaborative prediction ↗Jasson D. M. Rennie, Nathan Srebro939 citations
- A support vector method for multivariate performance measures ↗Thorsten Joachims786 citations
- Comparing clusterings ↗Marina Meilă589 citations
- Non-negative tensor factorization with applications to statistics and computer vision ↗Amnon Shashua, Tamir Hazan490 citations
- Near-optimal sensor placements in Gaussian processes ↗Carlos Guestrin, Andreas Krause, Ajit Paul Singh454 citations
- Learning structured prediction models ↗Ben Taskar, Vassil Chatalbashev, Daphne Koller et al.444 citations
- Beyond the point cloud ↗Vikas Sindhwani, Partha Niyogi, Mikhail Belkin439 citations
- Learning from labeled and unlabeled data on a directed graph ↗Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf403 citations
- High speed obstacle avoidance using monocular vision and reinforcement learning ↗Jeff Michels, Ashutosh Saxena, Andrew Ng394 citations
- Learning Gaussian processes from multiple tasks ↗Kai Yu, Volker Tresp, Anton Schwaighofer380 citations
- Preference learning with Gaussian processes ↗Wei Chu, Zoubin Ghahramani361 citations
- Bayesian hierarchical clustering ↗Katherine Heller, Zoubin Ghahramani357 citations
- Reinforcement learning with Gaussian processes ↗Yaakov Engel, Shie Mannor, Ron Meir335 citations
- The cross entropy method for classification ↗Shie Mannor, Dori Peleg A, Reuven Y. Rubinstein312 citations
- Naive Bayes models for probability estimation ↗Daniel Lowd, Pedro Domingos304 citations
- Learning the structure of Markov logic networks ↗Stanley Kok, Pedro Domingos298 citations
- Modeling word burstiness using the Dirichlet distribution ↗Rasmus Elsborg Madsen, David Kauchak, Charles Elkan280 citations
- New approaches to support vector ordinal regression ↗Wei Chu, S. Sathiya Keerthi277 citations
- Using additive expert ensembles to cope with concept drift ↗J. Zico Kolter, Marcus A. Maloof261 citations
- Identifying useful subgoals in reinforcement learning by local graph partitioning ↗Özgür Şimşek, Alicia P. Wolfe, Andrew G. Barto238 citations
- Predictive low-rank decomposition for kernel methods ↗Francis Bach, Michael I. Jordan238 citations
- Exploration and apprenticeship learning in reinforcement learning ↗Pieter Abbeel, Andrew Ng224 citations
- Supervised versus multiple instance learning ↗Soumya Ray, Mark W. Craven222 citations
- Supervised clustering with support vector machines ↗Thomas Finley, Thorsten Joachims212 citations
- Logistic regression with an auxiliary data source ↗Xuejun Liao, Ya Xue, Lawrence Carin203 citations
- Intrinsic dimensionality estimation of submanifolds in R d ↗Matthias Hein, Jean-Yves Audibert185 citations
- Integer linear programming inference for conditional random fields ↗Dan Roth, Wen-tau Yih179 citations
- Heteroscedastic Gaussian process regression ↗Quoc Viet Le, Alex J. Smola, Stéphane Canu175 citations
- Semi-supervised graph clustering ↗Brian Kulis, Sugato Basu, Inderjit S. Dhillon et al.174 citations
- Harmonic mixtures ↗Xiaojin Zhu, John Lafferty170 citations
- Learning as search optimization ↗Hal Daumé, Daniel Marcu157 citations
- Optimal assignment kernels for attributed molecular graphs ↗Holger Fröhlich, Jörg K. Wegner, Florian Sieker et al.145 citations
- Fast condensed nearest neighbor rule ↗Fabrizio Angiulli144 citations
- A theoretical analysis of Model-Based Interval Estimation ↗Alexander L. Strehl, Michael L. Littman135 citations
- Dynamic preferences in multi-criteria reinforcement learning ↗Sriraam Natarajan, Prasad V. Tadepalli132 citations
- Bounded real-time dynamic programming ↗H. Brendan McMahan, Maxim A. Likhachev, Geoffrey J. Gordon128 citations
- 2D Conditional Random Fields for Web information extraction ↗Jun Zhu, Zaiqing Nie, Ji-Rong Wen et al.124 citations
- Bayesian sparse sampling for on-line reward optimization ↗Tao Wang, Daniel J. Lizotte, Michael Bowling et al.114 citations
- Multi-way distributional clustering via pairwise interactions ↗Ron Bekkerman, Ran El‐Yaniv, Andrew McCallum105 citations
- Analysis and extension of spectral methods for nonlinear dimensionality reduction ↗Fei Sha, Lawrence K. Saul104 citations
- Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM ↗Sylvain Calinon, Aude Billard103 citations
- Proto-value functions ↗Sridhar Mahadevan94 citations
- Online learning over graphs ↗Mark Herbster, Massimiliano Pontil, L. J. Wainer93 citations
- Healing the relevance vector machine through augmentation ↗Carl Edward Rasmussen, Joaquin Quiñonero-Candela90 citations
- Learning hierarchical multi-category text classification models ↗Juho Rousu, Craig J. Saunders, Sándor Szedmák et al.90 citations
- Multi-instance tree learning ↗Hendrik Blockeel, David Page, Ashwin Srinivasan90 citations
- A general regression technique for learning transductions ↗Corinna Cortes, Mehryar Mohri, Jason Weston86 citations
- Hierarchic Bayesian models for kernel learning ↗Mark Girolami, Simon Rogers78 citations
- Learning predictive state representations in dynamical systems without reset ↗Britton Wolfe, Michael R. James, Satinder Pal Singh76 citations
- Statistical and computational analysis of locality preserving projection ↗Xiaofei He, Deng Cai, Wanli Min72 citations
- A martingale framework for concept change detection in time-varying data streams ↗Shen-Shyang Ho68 citations
- Discriminative versus generative parameter and structure learning of Bayesian network classifiers ↗Franz Pernkopf, Jeff Bilmes67 citations
- ROC confidence bands ↗Sofus A. Macskassy, Foster John Provost, Saharon Rosset66 citations
- A brain computer interface with online feedback based on magnetoencephalography ↗Thomas Navin Lal, Niels Birbaumer, Bernhard Schölkopf et al.65 citations
- Weighted decomposition kernels ↗Sauro Menchetti, Fabrizio Costa, Paolo Frasconi65 citations
- An efficient method for simplifying support vector machines ↗Duc-Dung Nguyen, Tu-Bao Ho63 citations
- Incomplete-data classification using logistic regression ↗David P. Williams, Xuejun Liao, Ya Xue et al.63 citations
- Clustering through ranking on manifolds ↗Markus Breitenbach, Gregory Z. Grudić59 citations
- Error limiting reductions between classification tasks ↗Alina Beygelzimer, Varsha Dani, Tom Hayes et al.59 citations
- Predicting relative performance of classifiers from samples ↗Rui Leite, Pavel Brazdil59 citations
- Finite time bounds for sampling based fitted value iteration ↗Csaba Szepesvári, Rémi Munos58 citations
- Q-learning of sequential attention for visual object recognition from informative local descriptors ↗Lucas Paletta, Gerald Fritz, Christin Seifert58 citations
- A new Mallows distance based metric for comparing clusterings ↗Ding Xuan Zhou, Jia Li, Hongyuan Zha57 citations
- Relating reinforcement learning performance to classification performance ↗John C. Langford, Bianca Zadrozny55 citations
- Optimizing abstaining classifiers using ROC analysis ↗Tadeusz Pietraszek54 citations
- Action respecting embedding ↗Michael Bowling, Ali Ghodsi, Dana F. Wilkinson53 citations
- Active learning for Hidden Markov Models ↗Brigham S. Anderson, Andrew Moore53 citations
- Evaluating machine learning for information extraction ↗Neil Ireson, Fabio Ciravegna, Mary Elaine Califf et al.53 citations
- Robust one-class clustering using hybrid global and local search ↗Gunjan Gupta, Joydeep Ghosh50 citations
- Large scale genomic sequence SVM classifiers ↗Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf47 citations
- Linear Asymmetric Classifier for cascade detectors ↗Jianxin Wu, Matthew D. Mullin, James Matthew Rehg47 citations
- Building Sparse Large Margin Classifiers ↗Mingrui Wu, Bernhard Schölkopf, Gökhan Bakır46 citations
- Core Vector Regression for very large regression problems ↗Ivor Wai-Hung Tsang, James Tin-Yau Kwok, Kimo T. Lai46 citations
- Multimodal oriented discriminant analysis ↗Fernando De la Torre, Takeo Kanade A46 citations
- Online feature selection for pixel classification ↗Karen A. Glocer, Damian R. Eads, James P. Theiler45 citations
- Learning to compete, compromise, and cooperate in repeated general-sum games ↗Jacob W. Crandall, Michael A. Goodrich42 citations
- A causal approach to hierarchical decomposition of factored MDPs ↗Anders Jönsson, Andrew G. Barto41 citations
- Expectation maximization algorithms for conditional likelihoods ↗Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski37 citations
- Learning approximate preconditions for methods in hierarchical plans ↗Okhtay Ilghami, Héctor Muñoz‐Avila, Dana S. Nau et al.37 citations
- Multi-class protein fold recognition using adaptive codes ↗Eugene Ie, Jason Weston, William Stafford Noble et al.36 citations
- Estimating and computing density based distance metrics ↗Sajama, Alon Orlitsky34 citations
- Predicting probability distributions for surf height using an ensemble of mixture density networks ↗Michael Carney, Pádraig Cunningham, Jim Dowling et al.34 citations
- Supervised dimensionality reduction using mixture models ↗Sajama, Alon Orlitsky33 citations
- Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes ↗Yushi Jing, Vladimir Pavlović, James Matthew Rehg32 citations
- Independent subspace analysis using geodesic spanning trees ↗Barnabás Póczos, András Lörincz32 citations
- Augmenting naive Bayes for ranking ↗Harry Zhang, Liangxiao Jiang, Jiang Su30 citations
- Learning predictive representations from a history ↗Eric Wiewiora30 citations
- Compact approximations to Bayesian predictive distributions ↗Edward Snelson, Zoubin Ghahramani28 citations
- Error bounds for correlation clustering ↗Thorsten Joachims, John E. Hopcroft28 citations
- Learning discontinuities with products-of-sigmoids for switching between local models ↗Marc Toussaint, Sethu Vijayakumar27 citations
- Learning first-order probabilistic models with combining rules ↗Sriraam Natarajan, Prasad V. Tadepalli, Eric E. Altendorf et al.27 citations
- Object correspondence as a machine learning problem ↗Bernhard Schölkopf, Florian Steinke, Volker Blanz27 citations
- Propagating distributions on a hypergraph by dual information regularization ↗Koji Tsuda25 citations
- Hierarchical Dirichlet model for document classification ↗Sriharsha Veeramachaneni, Diego Sona, Paolo Avesani23 citations
- Learn to weight terms in information retrieval using category information ↗Rong Jin, Joyce Yue Chai, Luo Si23 citations
- Combining model-based and instance-based learning for first order regression ↗Kurt Driessens, Sašo Džeroski22 citations
- Fast inference and learning in large-state-space HMMs ↗Sajid M. Siddiqi, Andrew Moore22 citations
- Unifying the error-correcting and output-code AdaBoost within the margin framework ↗Yijun Sun, Siniša Todorović, Jian Li et al.22 citations
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