ICML 2009: all accepted papers
- Multiple indefinite kernel learning with mixed norm regularization ↗Matthieu Kowalski, Marie Szafranski, Liva Ralaivola44 citations
- Proximal regularization for online and batch learning ↗Chuong B. Do, Quoc Viet Le, Chuan-Sheng Foo44 citations
- Accelerated sampling for the Indian Buffet Process ↗Finale Doshi‐Velez, Zoubin Ghahramani43 citations
- Sequential Bayesian prediction in the presence of changepoints ↗Roman Garnett, Michael A. Osborne, Stephen Roberts43 citations
- Model-free reinforcement learning as mixture learning ↗Nikos A. Vlassis, Marc Toussaint41 citations
- Surrogate regret bounds for proper losses ↗Mark D. Reid, Robert C. Williamson41 citations
- Partial order embedding with multiple kernels ↗Brian McFee, Gert R. G. Lanckriet40 citations
- A scalable framework for discovering coherent co-clusters in noisy data ↗Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh et al.39 citations
- ABC-boost ↗Ping Li38 citations
- Binary action search for learning continuous-action control policies ↗Jason Pazis, Michail G. Lagoudakis38 citations
- Learning complex motions by sequencing simpler motion templates ↗Gerhard M. Neumann, Wolfgang Maass, Jan Peters37 citations
- Partially supervised feature selection with regularized linear models ↗Thibault Helleputte, Pierre Dupont37 citations
- Polyhedral outer approximations with application to natural language parsing ↗André F. T. Martins, Noah A. Smith, Eric P. Xing35 citations
- Constraint relaxation in approximate linear programs ↗Marek Petrik, Shlomo Zilberstein B32 citations
- Convex variational Bayesian inference for large scale generalized linear models ↗Hannes Nickisch, Matthias Seeger32 citations
- Detecting the direction of causal time series ↗Jonas Peters, Dominik Janzing, Arthur Gretton et al.32 citations
- Online learning by ellipsoid method ↗Liu Yang, Rong Jin, Jieping Ye32 citations
- Structure learning with independent non-identically distributed data ↗Robert E. Tillman32 citations
- Invited talk: Can learning kernels help performance? ↗Corinna Cortes31 citations
- Learning nonlinear dynamic models ↗John C. Langford, Ruslan Salakhutdinov, Tong Zhang30 citations
- Sparse higher order conditional random fields for improved sequence labeling ↗Xian Qian, Xiaoqian Jiang, Qi Zhang et al.30 citations
- Function factorization using warped Gaussian processes ↗Mikkel Nørgaard Schmidt29 citations
- Geometry-aware metric learning ↗Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon27 citations
- Independent factor topic models ↗Duangmanee Putthividhya, Hagai T. Attias, Srikantan S. Nagarajan27 citations
- SimpleNPKL ↗Jinfeng Zhuang, Ivor Wai-Hung Tsang, Steven C. H. Hoi27 citations
- GAODE and HAODE ↗M. Julia Flores, José Antonio Gámez, Ana María Martínez et al.25 citations
- Ranking interesting subgroups ↗Stefan Rueping24 citations
- A majorization-minimization algorithm for (multiple) hyperparameter learning ↗Chuan-Sheng Foo, Chuong B. Do, Andrew Ng23 citations
- Nonparametric estimation of the precision-recall curve ↗Stéphan Clémençon, Nicolas Vayatis23 citations
- Route kernels for trees ↗Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti23 citations
- Approximate inference for planning in stochastic relational worlds ↗Tobias Lang, Marc Toussaint21 citations
- Discovering options from example trajectories ↗Peng Zang, Peng Zhou, David C. Minnen et al.21 citations
- Optimal reverse prediction ↗Linli Xu, Martha White, Dale Schuurmans21 citations
- Unsupervised search-based structured prediction ↗Hal Daumé21 citations
- Unsupervised hierarchical modeling of locomotion styles ↗Wei Pan, Lorenzo Torresani20 citations
- Fast evolutionary maximum margin clustering ↗Fabian Cristian Gieseke, Tapio Pahikkala, Oliver Krämer19 citations
- Optimistic initialization and greediness lead to polynomial time learning in factored MDPs ↗István Szita, András Lörincz19 citations
- Online feature elicitation in interactive optimization ↗Craig E. Boutilier, Kevin Regan, Paolo Viappiani18 citations
- Optimized expected information gain for nonlinear dynamical systems ↗Alberto Giovanni Busetto, Cheng Soon Ong, Joachim M. Buhmann18 citations
- Archipelago ↗Ryan Prescott Adams, Zoubin Ghahramani17 citations
- Discriminative k -metrics ↗Arthur D. Szlam, Guillermo Sapiro17 citations
- Learning when to stop thinking and do something! ↗Barnabás Póczos, Yasin Abbasi-Yadkori, Csaba Szepesvári et al.16 citations
- Workshop summary: The fourth workshop on evaluation methods for machine learning ↗Chris Drummond, Nathalie Japkowicz, William Klement et al.16 citations
- Tutorial summary: Active learning ↗Sanjoy Dasgupta, John C. Langford15 citations
- Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties ↗Ondřej Kuželka, Filip Železný12 citations
- Split variational inference ↗Guillaume Bouchard, Onno R. Zoeter12 citations
- Bayesian clustering for email campaign detection ↗Peter Haider, Tobias Scheffer11 citations
- K-means in space ↗Kiri L. Wagstaff, Benjamin Bornstein11 citations
- Matrix updates for perceptron training of continuous density hidden Markov models ↗Chih‐Chieh Cheng, Fei Sha, Lawrence K. Saul11 citations
- Active learning for directed exploration of complex systems ↗Michael C. Burl, Esther Wang10 citations
- Learning structurally consistent undirected probabilistic graphical models ↗Sushmita Mimi Roy, Terran D.R. Lane, Margaret Werner‐Washburne10 citations
- Learning to segment from a few well-selected training images ↗Alireza Farhangfar, Russell Greiner, Csaba Szepesvári9 citations
- Predictive representations for policy gradient in POMDPs ↗Abdeslam Boularias, Brahim Chaib-draa9 citations
- A simpler unified analysis of budget perceptrons ↗Ilya Sutskever8 citations
- Learning dictionaries of stable autoregressive models for audio scene analysis ↗Youngmin Cho, Lawrence K. Saul8 citations
- On primal and dual sparsity of Markov networks ↗Jun Zhu, Eric P. Xing7 citations
- Learning linear dynamical systems without sequence information ↗Tzu-Kuo Huang, Jeff Schneider6 citations
- Orbit-product representation and correction of Gaussian belief propagation ↗Jason K. Johnson, Vladimir Chernyak, Michael Chertkov6 citations
- A Bayesian approach to protein model quality assessment ↗Hetunandan Kamisetty, CHRISTOPHER JAMES LANGMEAD5 citations
- Tutorial summary: Large social and information networks ↗Jure Leskovec5 citations
- Tutorial summary: The neuroscience of reinforcement learning ↗Yael Niv5 citations
- Exploiting sparse Markov and covariance structure in multiresolution models ↗Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky4 citations
- Proto-predictive representation of states with simple recurrent temporal-difference networks ↗Takaki Makino4 citations
- Tutorial summary: Learning with dependencies between several response variables ↗Volker Tresp, Kai Yu4 citations
- Invited talk: Drifting games, boosting and online learning ↗Yoav Freund2 citations
- Workshop summary: Abstraction in reinforcement learning ↗Özgür Şimşek2 citations
- Workshop summary: Results of the 2009 reinforcement learning competition ↗David Wingate, Carlos Diuk, Lihong Li et al.2 citations
- Workshop summary: Workshop on learning feature hierarchies ↗Kay Yu, Ruslan Salakhutdinov, Yann LeCun et al.2 citations
- Learning prediction suffix trees with Winnow ↗Nikos Karampatziakis, Dexter C. Kozen1 citation
- Stochastic methods for {ıt l}1 regularized loss minimization ↗Shai Shalev‐Shwartz, Ambuj Tewari1 citation
- Tutorial summary: Reductions in machine learning ↗Alina Beygelzimer, John C. Langford, Bianca Zadrozny1 citation
- Tutorial summary: Survey of boosting from an optimization perspective ↗Manfred K. Warmuth, S. V. N. Vishwanathan1 citation
- Workshop summary: Automated interpretation and modelling of cell images ↗Robert F. Murphy, Chun‐Nan Hsu, Loris Nanni1 citation
- Compositional noisy-logical learning ↗Alan Yuille, Songfeng Zheng
- Tutorial summary: Convergence of natural dynamics to equilibria ↗Eyal Even-Dar, Vahab Mirrokni
- Tutorial summary: Machine learning in IR ↗Paul N. Bennett, Misha Bilenko, Kevyn Collins‐Thompson
- Workshop summary: Numerical mathematics in machine learning ↗Matthias Seeger, Suvrit Sra, John P. Cunningham
- Workshop summary: On-line learning with limited feedback ↗Jean-Yves Audibert, Peter L. Auer, Alessandro Lazaric et al.
- Workshop summary: Seventh annual workshop on Bayes applications ↗John Mark Agosta, Russell G. Almond, Dennis M. Buede et al.
- Workshop summary: Sparse methods for music audio ↗Douglas Eck, Daniel P. W. Ellis, Philippe Hamel
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