ICML A*

181 papers

YearTitle / Authors
2009A Bayesian approach to protein model quality assessment.
Hetunandan Kamisetty, Christopher James Langmead
2009A convex formulation for learning shared structures from multiple tasks.
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
2009A least squares formulation for a class of generalized eigenvalue problems in machine learning.
Liang Sun, Shuiwang Ji, Jieping Ye
2009A majorization-minimization algorithm for (multiple) hyperparameter learning.
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
2009A novel lexicalized HMM-based learning framework for web opinion mining.
2009A scalable framework for discovering coherent co-clusters in noisy data.
Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk Cho, Inderjit S. Dhillon
2009A simpler unified analysis of budget perceptrons.
Ilya Sutskever
2009A stochastic memoizer for sequence data.
Frank D. Wood, Cédric Archambeau, Jan Gasthaus, Lancelot James, Yee Whye Teh
2009ABC-boost: adaptive base class boost for multi-class classification.
Ping Li
2009Accelerated sampling for the Indian Buffet Process.
Finale Doshi-Velez, Zoubin Ghahramani
2009Accounting for burstiness in topic models.
Gabriel Doyle, Charles Elkan
2009Active learning for directed exploration of complex systems.
Michael C. Burl, Esther Wang
2009An accelerated gradient method for trace norm minimization.
Shuiwang Ji, Jieping Ye
2009An efficient projection for
Ariadna Quattoni, Xavier Carreras, Michael Collins, Trevor Darrell
2009An efficient sparse metric learning in high-dimensional space via
Guo-Jun Qi, Jinhui Tang, Zheng-Jun Zha, Tat-Seng Chua, Hong-Jiang Zhang
2009Analytic moment-based Gaussian process filtering.
Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hanebeck
2009Approximate inference for planning in stochastic relational worlds.
Tobias Lang, Marc Toussaint
2009Archipelago: nonparametric Bayesian semi-supervised learning.
Ryan Prescott Adams, Zoubin Ghahramani
2009Bandit-based optimization on graphs with application to library performance tuning.
Frédéric de Mesmay, Arpad Rimmel, Yevgen Voronenko, Markus Püschel
2009Bayesian clustering for email campaign detection.
Peter Haider, Tobias Scheffer
2009Bayesian inference for Plackett-Luce ranking models.
John Guiver, Edward Lloyd Snelson
2009Binary action search for learning continuous-action control policies.
Jason Pazis, Michail G. Lagoudakis
2009Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties.
Ondrej Kuzelka, Filip Zelezný
2009Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery.
Han Liu, Mark Palatucci, Jian Zhang
2009BoltzRank: learning to maximize expected ranking gain.
Maksims Volkovs, Richard S. Zemel
2009Boosting products of base classifiers.
Balázs Kégl, Róbert Busa-Fekete
2009Boosting with structural sparsity.
John C. Duchi, Yoram Singer
2009Compositional noisy-logical learning.
Alan L. Yuille, Songfeng Zheng
2009Constraint relaxation in approximate linear programs.
Marek Petrik, Shlomo Zilberstein
2009Convex variational Bayesian inference for large scale generalized linear models.
Hannes Nickisch, Matthias W. Seeger
2009Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations.
Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
2009Curriculum learning.
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston
2009Decision tree and instance-based learning for label ranking.
Weiwei Cheng, Jens C. Huhn, Eyke Hüllermeier
2009Deep learning from temporal coherence in video.
Hossein Mobahi, Ronan Collobert, Jason Weston
2009Deep transfer via second-order Markov logic.
Jesse Davis, Pedro M. Domingos
2009Detecting the direction of causal time series.
Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf
2009Discovering options from example trajectories.
Peng Zang, Peng Zhou, David Minnen, Charles Lee Isbell Jr.
2009Discriminative
Arthur Szlam, Guillermo Sapiro
2009Domain adaptation from multiple sources via auxiliary classifiers.
Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua
2009Dynamic analysis of multiagent
Eduardo Rodrigues Gomes, Ryszard Kowalczyk
2009Dynamic mixed membership blockmodel for evolving networks.
Wenjie Fu, Le Song, Eric P. Xing
2009Efficient Euclidean projections in linear time.
Jun Liu, Jieping Ye
2009Efficient learning algorithms for changing environments.
Elad Hazan, C. Seshadhri
2009EigenTransfer: a unified framework for transfer learning.
Wenyuan Dai, Ou Jin, Gui-Rong Xue, Qiang Yang, Yong Yu
2009Evaluation methods for topic models.
Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno
2009Exploiting sparse Markov
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky
2009Factored conditional restricted Boltzmann Machines for modeling motion style.
Graham W. Taylor, Geoffrey E. Hinton
2009Fast evolutionary maximum margin clustering.
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
2009Fast gradient-descent methods for temporal-difference learning with linear function approximation.
Richard S. Sutton, Hamid Reza Maei, Doina Precup, Shalabh Bhatnagar, David Silver, Csaba Szepesvári, Eric Wiewiora
2009Feature hashing for large scale multitask learning.
Kilian Q. Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, Josh Attenberg
2009Fitting a graph to vector data.
Samuel I. Daitch, Jonathan A. Kelner, Daniel A. Spielman
2009Function factorization using warped Gaussian processes.
Mikkel N. Schmidt
2009GAODE and HAODE: two proposals based on AODE to deal with continuous variables.
M. Julia Flores, José A. Gámez, Ana M. Martínez, José M. Puerta
2009Generalization analysis of listwise learning-to-rank algorithms.
Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li
2009Geometry-aware metric learning.
Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon
2009Good learners for evil teachers.
Ofer Dekel, Ohad Shamir
2009Gradient descent with sparsification: an iterative algorithm for sparse recovery with restricted isometry property.
Rahul Garg, Rohit Khandekar
2009Grammatical inference as a principal component analysis problem.
Raphaël Bailly, François Denis, Liva Ralaivola
2009Graph construction and
Tony Jebara, Jun Wang, Shih-Fu Chang
2009Group lasso with overlap and graph lasso.
Laurent Jacob, Guillaume Obozinski, Jean-Philippe Vert
2009Herding dynamical weights to learn.
Max Welling
2009Hilbert space embeddings of conditional distributions with applications to dynamical systems.
Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu
2009Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search.
Verena Heidrich-Meisner, Christian Igel
2009Identifying suspicious URLs: an application of large-scale online learning.
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
2009Importance weighted active learning.
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
2009Incorporating domain knowledge into topic modeling via Dirichlet Forest priors.
David Andrzejewski, Xiaojin Zhu, Mark Craven
2009Independent factor topic models.
Duangmanee Putthividhya, Hagai Thomas Attias, Srikantan S. Nagarajan
2009Information theoretic measures for clusterings comparison: is a correction for chance necessary?
Xuan Vinh Nguyen, Julien Epps, James Bailey
2009Interactively optimizing information retrieval systems as a dueling bandits problem.
Yisong Yue, Thorsten Joachims
2009Invited talk: Can learning kernels help performance?
Corinna Cortes
2009Invited talk: Drifting games, boosting and online learning.
Yoav Freund
2009K-means in space: a radiation sensitivity evaluation.
Kiri L. Wagstaff, Benjamin J. Bornstein
2009Kernelized value function approximation for reinforcement learning.
Gavin Taylor, Ronald Parr
2009Large margin training for hidden Markov models with partially observed states.
Trinh Minh Tri Do, Thierry Artières
2009Large-scale collaborative prediction using a nonparametric random effects model.
Kai Yu, John D. Lafferty, Shenghuo Zhu, Yihong Gong
2009Large-scale deep unsupervised learning using graphics processors.
Rajat Raina, Anand Madhavan, Andrew Y. Ng
2009Learning Markov logic network structure via hypergraph lifting.
Stanley Kok, Pedro M. Domingos
2009Learning complex motions by sequencing simpler motion templates.
Gerhard Neumann, Wolfgang Maass, Jan Peters
2009Learning dictionaries of stable autoregressive models for audio scene analysis.
Youngmin Cho, Lawrence K. Saul
2009Learning from measurements in exponential families.
Percy Liang, Michael I. Jordan, Dan Klein
2009Learning instance specific distances using metric propagation.
De-Chuan Zhan, Ming Li, Yufeng Li, Zhi-Hua Zhou
2009Learning kernels from indefinite similarities.
Yihua Chen, Maya R. Gupta, Benjamin Recht
2009Learning linear dynamical systems without sequence information.
Tzu-Kuo Huang, Jeff G. Schneider
2009Learning non-redundant codebooks for classifying complex objects.
Wei Zhang, Akshat Surve, Xiaoli Z. Fern, Thomas G. Dietterich
2009Learning nonlinear dynamic models.
John Langford, Ruslan Salakhutdinov, Tong Zhang
2009Learning prediction suffix trees with Winnow.
Nikolaos Karampatziakis, Dexter Kozen
2009Learning spectral graph transformations for link prediction.
Jérôme Kunegis, Andreas Lommatzsch
2009Learning structural SVMs with latent variables.
Chun-Nam John Yu, Thorsten Joachims
2009Learning structurally consistent undirected probabilistic graphical models.
Sushmita Roy, Terran Lane, Margaret Werner-Washburne
2009Learning to segment from a few well-selected training images.
Alireza Farhangfar, Russell Greiner, Csaba Szepesvári
2009Learning when to stop thinking and do something!
Barnabás Póczos, Yasin Abbasi-Yadkori, Csaba Szepesvári, Russell Greiner, Nathan R. Sturtevant
2009Learning with structured sparsity.
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
2009Matrix updates for perceptron training of continuous density hidden Markov models.
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
2009MedLDA: maximum margin supervised topic models for regression and classification.
Jun Zhu, Amr Ahmed, Eric P. Xing
2009Model-free reinforcement learning as mixture learning.
Nikos Vlassis, Marc Toussaint
2009Monte-Carlo simulation balancing.
David Silver, Gerald Tesauro
2009More generality in efficient multiple kernel learning.
Manik Varma, Bodla Rakesh Babu
2009Multi-assignment clustering for Boolean data.
Andreas P. Streich, Mario Frank, David A. Basin, Joachim M. Buhmann
2009Multi-class image segmentation using conditional random fields and global classification.
Nils Plath, Marc Toussaint, Shinichi Nakajima
2009Multi-instance learning by treating instances as non-I.I.D. samples.
Zhi-Hua Zhou, Yu-Yin Sun, Yufeng Li
2009Multi-view clustering via canonical correlation analysis.
Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan
2009Multiple indefinite kernel learning with mixed norm regularization.
Matthieu Kowalski, Marie Szafranski, Liva Ralaivola
2009Near-Bayesian exploration in polynomial time.
J. Zico Kolter, Andrew Y. Ng
2009Nearest neighbors in high-dimensional data: the emergence and influence of hubs.
Milos Radovanovic, Alexandros Nanopoulos, Mirjana Ivanovic
2009Non-linear matrix factorization with Gaussian processes.
Neil D. Lawrence, Raquel Urtasun
2009Non-monotonic feature selection.
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King
2009Nonparametric estimation of the precision-recall curve.
Stéphan Clémençon, Nicolas Vayatis
2009Nonparametric factor analysis with beta process priors.
John W. Paisley, Lawrence Carin
2009On primal and dual sparsity of Markov networks.
Jun Zhu, Eric P. Xing
2009On sampling-based approximate spectral decomposition.
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
2009Online dictionary learning for sparse coding.
Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro
2009Online feature elicitation in interactive optimization.
Craig Boutilier, Kevin Regan, Paolo Viappiani
2009Online learning by ellipsoid method.
Liu Yang, Rong Jin, Jieping Ye
2009Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning.
Linli Xu, Martha White, Dale Schuurmans
2009Optimistic initialization and greediness lead to polynomial time learning in factored MDPs.
Istvan Szita, András Lörincz
2009Optimized expected information gain for nonlinear dynamical systems.
Alberto Giovanni Busetto, Cheng Soon Ong, Joachim M. Buhmann
2009Orbit-product representation and correction of Gaussian belief propagation.
Jason K. Johnson, Vladimir Y. Chernyak, Michael Chertkov
2009PAC-Bayesian learning of linear classifiers.
Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand
2009Partial order embedding with multiple kernels.
Brian McFee, Gert R. G. Lanckriet
2009Partially supervised feature selection with regularized linear models.
Thibault Helleputte, Pierre Dupont
2009Piecewise-stationary bandit problems with side observations.
Jia Yuan Yu, Shie Mannor
2009Polyhedral outer approximations with application to natural language parsing.
André F. T. Martins, Noah A. Smith, Eric P. Xing
2009Predictive representations for policy gradient in POMDPs.
Abdeslam Boularias, Brahim Chaib-draa
2009Probabilistic dyadic data analysis with local and global consistency.
Deng Cai, Xuanhui Wang, Xiaofei He
2009Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009
Andrea Pohoreckyj Danyluk, Léon Bottou, Michael L. Littman
2009Proto-predictive representation of states with simple recurrent temporal-difference networks.
Takaki Makino
2009Prototype vector machine for large scale semi-supervised learning.
Kai Zhang, James T. Kwok, Bahram Parvin
2009Proximal regularization for online and batch learning.
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
2009Ranking interesting subgroups.
Stefan Rüping
2009Ranking with ordered weighted pairwise classification.
Nicolas Usunier, David Buffoni, Patrick Gallinari
2009Regression by dependence minimization and its application to causal inference in additive noise models.
Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schölkopf
2009Regularization and feature selection in least-squares temporal difference learning.
J. Zico Kolter, Andrew Y. Ng
2009Robot trajectory optimization using approximate inference.
Marc Toussaint
2009Robust bounds for classification via selective sampling.
Nicolò Cesa-Bianchi, Claudio Gentile, Francesco Orabona
2009Robust feature extraction via information theoretic learning.
Xiaotong Yuan, Bao-Gang Hu
2009Route kernels for trees.
Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti
2009Rule learning with monotonicity constraints.
Wojciech Kotlowski, Roman Slowinski
2009Semi-supervised learning using label mean.
Yufeng Li, James T. Kwok, Zhi-Hua Zhou
2009Sequential Bayesian prediction in the presence of changepoints.
Roman Garnett, Michael A. Osborne, Stephen J. Roberts
2009SimpleNPKL: simple non-parametric kernel learning.
Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi
2009Solution stability in linear programming relaxations: graph partitioning and unsupervised learning.
Sebastian Nowozin, Stefanie Jegelka
2009Sparse Gaussian graphical models with unknown block structure.
Benjamin M. Marlin, Kevin P. Murphy
2009Sparse higher order conditional random fields for improved sequence labeling.
Xian Qian, Xiaoqian Jiang, Qi Zhang, Xuanjing Huang, Lide Wu
2009Spectral clustering based on the graph
Thomas Bühler, Matthias Hein
2009Split variational inference.
Guillaume Bouchard, Onno Zoeter
2009Stochastic methods for
Shai Shalev-Shwartz, Ambuj Tewari
2009Stochastic search using the natural gradient.
Yi Sun, Daan Wierstra, Tom Schaul, Jürgen Schmidhuber
2009Structure learning of Bayesian networks using constraints.
Cassio P. de Campos, Zhi Zeng, Qiang Ji
2009Structure learning with independent non-identically distributed data.
Robert E. Tillman
2009Structure preserving embedding.
Blake Shaw, Tony Jebara
2009Supervised learning from multiple experts: whom to trust when everyone lies a bit.
Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Anna K. Jerebko, Charles Florin, Gerardo Hermosillo Valadez, Luca Bogoni, Linda Moy
2009Surrogate regret bounds for proper losses.
Mark D. Reid, Robert C. Williamson
2009The Bayesian group-Lasso for analyzing contingency tables.
Sudhir Raman, Thomas J. Fuchs, Peter J. Wild, Edgar Dahl, Volker Roth
2009The adaptive
Carlos Diuk, Lihong Li, Bethany R. Leffler
2009The graphlet spectrum.
Risi Kondor, Nino Shervashidze, Karsten M. Borgwardt
2009Topic-link LDA: joint models of topic and author community.
Yan Liu, Alexandru Niculescu-Mizil, Wojciech Gryc
2009Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities.
Ryan Prescott Adams, Iain Murray, David J. C. MacKay
2009Trajectory prediction: learning to map situations to robot trajectories.
Nikolay Jetchev, Marc Toussaint
2009Transfer learning for collaborative filtering via a rating-matrix generative model.
Bin Li, Qiang Yang, Xiangyang Xue
2009Tutorial summary: Active learning.
Sanjoy Dasgupta, John Langford
2009Tutorial summary: Convergence of natural dynamics to equilibria.
Eyal Even-Dar, Vahab S. Mirrokni
2009Tutorial summary: Large social and information networks: opportunities for ML.
Jure Leskovec
2009Tutorial summary: Learning with dependencies between several response variables.
Volker Tresp, Kai Yu
2009Tutorial summary: Machine learning in IR: recent successes and new opportunities.
Paul N. Bennett, Misha Bilenko, Kevyn Collins-Thompson
2009Tutorial summary: Reductions in machine learning.
Alina Beygelzimer, John Langford, Bianca Zadrozny
2009Tutorial summary: Structured prediction for natural language processing.
Noah A. Smith
2009Tutorial summary: Survey of boosting from an optimization perspective.
Manfred K. Warmuth, S. V. N. Vishwanathan
2009Tutorial summary: The neuroscience of reinforcement learning.
Yael Niv
2009Uncertainty sampling and transductive experimental design for active dual supervision.
Vikas Sindhwani, Prem Melville, Richard D. Lawrence
2009Unsupervised hierarchical modeling of locomotion styles.
Wei Pan, Lorenzo Torresani
2009Unsupervised search-based structured prediction.
Hal Daumé III
2009Using fast weights to improve persistent contrastive divergence.
Tijmen Tieleman, Geoffrey E. Hinton
2009Workshop summary: Abstraction in reinforcement learning.
Özgür Simsek
2009Workshop summary: Automated interpretation and modelling of cell images.
Robert F. Murphy, Chun-Nan Hsu, Loris Nanni
2009Workshop summary: Numerical mathematics in machine learning.
Matthias W. Seeger, Suvrit Sra, John P. Cunningham
2009Workshop summary: On-line learning with limited feedback.
Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári
2009Workshop summary: Results of the 2009 reinforcement learning competition.
David Wingate, Carlos Diuk, Lihong Li, Matthew Taylor, Jordan Frank
2009Workshop summary: Seventh annual workshop on Bayes applications.
John Mark Agosta, Russell G. Almond, Dennis M. Buede, Marek J. Druzdzel, Judy Goldsmith, Silja Renooij
2009Workshop summary: Sparse methods for music audio.
Douglas Eck, Dan Ellis, Philippe Hamel
2009Workshop summary: The fourth workshop on evaluation methods for machine learning.
Chris Drummond, Nathalie Japkowicz, William Klement, Sofus A. Macskassy
2009Workshop summary: Workshop on learning feature hierarchies.
Kai Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio