ICML A*

140 papers

YearTitle / Authors
2006A DC-programming algorithm for kernel selection.
Andreas Argyriou, Raphael Hauser, Charles A. Micchelli, Massimiliano Pontil
2006A choice model with infinitely many latent features.
Dilan Görür, Frank Jäkel, Carl Edward Rasmussen
2006A continuation method for semi-supervised SVMs.
Olivier Chapelle, Mingmin Chi, Alexander Zien
2006A duality view of spectral methods for dimensionality reduction.
Lin Xiao, Jun Sun, Stephen P. Boyd
2006A graphical model for predicting protein molecular function.
Barbara E. Engelhardt, Michael I. Jordan, Steven E. Brenner
2006A new approach to data driven clustering.
Arik Azran, Zoubin Ghahramani
2006A note on mixtures of experts for multiclass responses: approximation rate and Consistent Bayesian Inference.
Yang Ge, Wenxin Jiang
2006A probabilistic model for text kernels.
Alain D. Lehmann, John Shawe-Taylor
2006A regularization framework for multiple-instance learning.
Pak-Ming Cheung, James T. Kwok
2006A statistical approach to rule learning.
Ulrich Rückert, Stefan Kramer
2006Accelerated training of conditional random fields with stochastic gradient methods.
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
2006Active learning via transductive experimental design.
Kai Yu, Jinbo Bi, Volker Tresp
2006Active sampling for detecting irrelevant features.
Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo Avesani
2006Agnostic active learning.
Maria-Florina Balcan, Alina Beygelzimer, John Langford
2006Algorithms for portfolio management based on the Newton method.
Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. Schapire
2006An analysis of graph cut size for transductive learning.
Steve Hanneke
2006An analytic solution to discrete Bayesian reinforcement learning.
Pascal Poupart, Nikos Vlassis, Jesse Hoey, Kevin Regan
2006An empirical comparison of supervised learning algorithms.
Rich Caruana, Alexandru Niculescu-Mizil
2006An intrinsic reward mechanism for efficient exploration.
Özgür Simsek, Andrew G. Barto
2006An investigation of computational and informational limits in Gaussian mixture clustering.
Nathan Srebro, Gregory Shakhnarovich, Sam T. Roweis
2006Automatic basis function construction for approximate dynamic programming and reinforcement learning.
Philipp W. Keller, Shie Mannor, Doina Precup
2006Autonomous shaping: knowledge transfer in reinforcement learning.
George Dimitri Konidaris, Andrew G. Barto
2006Batch mode active learning and its application to medical image classification.
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
2006Bayesian learning of measurement and structural models.
Ricardo Bezerra de Andrade e Silva, Richard Scheines
2006Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture.
Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Yee Whye Teh
2006Bayesian pattern ranking for move prediction in the game of Go.
David H. Stern, Ralf Herbrich, Thore Graepel
2006Bayesian regression with input noise for high dimensional data.
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
2006Block-quantized kernel matrix for fast spectral embedding.
Kai Zhang, James T. Kwok
2006CN = CPCN.
Liva Ralaivola, François Denis, Christophe Nicolas Magnan
2006Categorization in multiple category systems.
Jean-Michel Renders, Éric Gaussier, Cyril Goutte, François Pacull, Gabriela Csurka
2006Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features.
Le Song, Julien Epps
2006Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution.
Charles Elkan
2006Clustering graphs by weighted substructure mining.
Koji Tsuda, Taku Kudo
2006Collaborative ordinal regression.
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
2006Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations.
Dennis DeCoste
2006Combined central and subspace clustering for computer vision applications.
Le Lu, René Vidal
2006Combining discriminative features to infer complex trajectories.
David A. Ross, Simon Osindero, Richard S. Zemel
2006Concept boundary detection for speeding up SVMs.
Navneet Panda, Edward Y. Chang, Gang Wu
2006Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks.
Alex Graves, Santiago Fernández, Faustino J. Gomez, Jürgen Schmidhuber
2006Constructing informative priors using transfer learning.
Rajat Raina, Andrew Y. Ng, Daphne Koller
2006Convex optimization techniques for fitting sparse Gaussian graphical models.
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont, Georges Natsoulis
2006Cost-sensitive learning with conditional Markov networks.
Prithviraj Sen, Lise Getoor
2006Cover trees for nearest neighbor.
Alina Beygelzimer, Sham M. Kakade, John Langford
2006Data association for topic intensity tracking.
Andreas Krause, Jure Leskovec, Carlos Guestrin
2006Dealing with non-stationary environments using context detection.
Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel
2006Deterministic annealing for semi-supervised kernel machines.
Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle
2006Discriminative cluster analysis.
Fernando De la Torre, Takeo Kanade
2006Discriminative unsupervised learning of structured predictors.
Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dale Schuurmans
2006Dynamic topic models.
David M. Blei, John D. Lafferty
2006Efficient MAP approximation for dense energy functions.
Marius Leordeanu, Martial Hebert
2006Efficient co-regularised least squares regression.
Ulf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel
2006Efficient inference on sequence segmentation models.
Sunita Sarawagi
2006Efficient lazy elimination for averaged one-dependence estimators.
Fei Zheng, Geoffrey I. Webb
2006Efficient learning of Naive Bayes classifiers under class-conditional classification noise.
François Denis, Christophe Nicolas Magnan, Liva Ralaivola
2006Estimating relatedness via data compression.
Brendan Juba
2006Experience-efficient learning in associative bandit problems.
Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh
2006Fast and space efficient string kernels using suffix arrays.
Choon Hui Teo, S. V. N. Vishwanathan
2006Fast direct policy evaluation using multiscale analysis of Markov diffusion processes.
Mauro Maggioni, Sridhar Mahadevan
2006Fast nonparametric clustering with Gaussian blurring mean-shift.
Miguel Á. Carreira-Perpiñán
2006Fast particle smoothing: if I had a million particles.
Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang
2006Fast time series classification using numerosity reduction.
Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton, Li Wei, Chotirat Ann Ratanamahatana
2006Fast transpose methods for kernel learning on sparse data.
Patrick Haffner
2006Feature subset selection bias for classification learning.
Surendra K. Singhi, Huan Liu
2006Feature value acquisition in testing: a sequential batch test algorithm.
Victor S. Sheng, Charles X. Ling
2006Full Bayesian network classifiers.
Jiang Su, Harry Zhang
2006Generalized spectral bounds for sparse LDA.
Baback Moghaddam, Yair Weiss, Shai Avidan
2006Graph model selection using maximum likelihood.
Ivona Bezáková, Adam Kalai, Rahul Santhanam
2006Hidden process models.
Rebecca A. Hutchinson, Tom M. Mitchell, Indrayana Rustandi
2006Hierarchical classification: combining Bayes with SVM.
Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
2006Higher order learning with graphs.
Sameer Agarwal, Kristin Branson, Serge J. Belongie
2006How boosting the margin can also boost classifier complexity.
Lev Reyzin, Robert E. Schapire
2006Inference with the Universum.
Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik
2006Iterative RELIEF for feature weighting.
Yijun Sun, Jian Li
2006Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems.
David Wingate, Satinder Singh
2006Kernel information embeddings.
Roland Memisevic
2006Kernelizing the output of tree-based methods.
Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc
2006Label propagation through linear neighborhoods.
Fei Wang, Changshui Zhang
2006Learning a kernel function for classification with small training samples.
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
2006Learning algorithms for online principal-agent problems (and selling goods online).
Vincent Conitzer, Nikesh Garera
2006Learning hierarchical task networks by observation.
Negin Nejati, Pat Langley, Tolga Könik
2006Learning high-order MRF priors of color images.
Julian J. McAuley, Tibério S. Caetano, Alexander J. Smola, Matthias O. Franz
2006Learning low-rank kernel matrices.
Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
2006Learning predictive state representations using non-blind policies.
Michael H. Bowling, Peter McCracken, Michael James, James Neufeld, Dana F. Wilkinson
2006Learning the structure of Factored Markov Decision Processes in reinforcement learning problems.
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin
2006Learning to impersonate.
Moni Naor, Guy N. Rothblum
2006Learning user preferences for sets of objects.
Marie desJardins, Eric Eaton, Kiri Wagstaff
2006Local Fisher discriminant analysis for supervised dimensionality reduction.
Masashi Sugiyama
2006Local distance preservation in the GP-LVM through back constraints.
Neil D. Lawrence, Joaquin Quiñonero Candela
2006Locally adaptive classification piloted by uncertainty.
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwok
2006Looping suffix tree-based inference of partially observable hidden state.
Michael P. Holmes, Charles Lee Isbell Jr.
2006MISSL: multiple-instance semi-supervised learning.
Rouhollah Rahmani, Sally A. Goldman
2006Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006
William W. Cohen, Andrew W. Moore
2006Maximum margin planning.
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinkevich
2006Multiclass boosting with repartitioning.
Ling Li
2006Multiclass reduced-set support vector machines.
Benyang Tang, Dominic Mazzoni
2006Nightmare at test time: robust learning by feature deletion.
Amir Globerson, Sam T. Roweis
2006Nonstationary kernel combination.
Darrin P. Lewis, Tony Jebara, William Stafford Noble
2006Null space versus orthogonal linear discriminant analysis.
Jieping Ye, Tao Xiong
2006On Bayesian bounds.
Arindam Banerjee
2006On a theory of learning with similarity functions.
Maria-Florina Balcan, Avrim Blum
2006Online decoding of Markov models under latency constraints.
Mukund Narasimhan, Paul A. Viola, Michael Shilman
2006Online multiclass learning by interclass hypothesis sharing.
Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman
2006Optimal kernel selection in Kernel Fisher discriminant analysis.
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boyd
2006PAC model-free reinforcement learning.
Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman
2006Pachinko allocation: DAG-structured mixture models of topic correlations.
Wei Li, Andrew McCallum
2006Pareto optimal linear classification.
Seung-Jean Kim, Alessandro Magnani, Sikandar Samar, Stephen P. Boyd, Johan Lim
2006Permutation invariant SVMs.
Pannagadatta K. Shivaswamy, Tony Jebara
2006Personalized handwriting recognition via biased regularization.
Wolf Kienzle, Kumar Chellapilla
2006Practical solutions to the problem of diagonal dominance in kernel document clustering.
Derek Greene, Padraig Cunningham
2006Predictive linear-Gaussian models of controlled stochastic dynamical systems.
Matthew R. Rudary, Satinder Singh
2006Predictive search distributions.
Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle
2006Predictive state representations with options.
Britton Wolfe, Satinder Singh
2006Probabilistic inference for solving discrete and continuous state Markov Decision Processes.
Marc Toussaint, Amos J. Storkey
2006Pruning in ordered bagging ensembles.
Gonzalo Martínez-Muñoz, Alberto Suárez
2006Quadratic programming relaxations for metric labeling and Markov random field MAP estimation.
Pradeep Ravikumar, John D. Lafferty
2006Qualitative reinforcement learning.
Arkady Epshteyn, Gerald DeJong
2006Ranking individuals by group comparisons.
Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng
2006Ranking on graph data.
Shivani Agarwal
2006Region-based value iteration for partially observable Markov decision processes.
Hui Li, Xuejun Liao, Lawrence Carin
2006Regression with the optimised combination technique.
Jochen Garcke
2006Reinforcement learning for optimized trade execution.
Yuriy Nevmyvaka, Yi Feng, Michael J. Kearns
2006Relational temporal difference learning.
Nima Asgharbeygi, David J. Stracuzzi, Pat Langley
2006Robust Euclidean embedding.
Lawrence Cayton, Sanjoy Dasgupta
2006Robust probabilistic projections.
Cédric Archambeau, Nicolas Delannay, Michel Verleysen
2006Semi-supervised learning for structured output variables.
Ulf Brefeld, Tobias Scheffer
2006Semi-supervised nonlinear dimensionality reduction.
Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlow
2006Sequential update of ADtrees.
Josep Roure, Andrew W. Moore
2006Simpler knowledge-based support vector machines.
Quoc V. Le, Alexander J. Smola, Thomas Gärtner
2006Spectral clustering for multi-type relational data.
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu
2006Statistical debugging: simultaneous identification of multiple bugs.
Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik, Alex Aiken
2006The rate adapting poisson model for information retrieval and object recognition.
Peter V. Gehler, Alex Holub, Max Welling
2006The relationship between Precision-Recall and ROC curves.
Jesse Davis, Mark H. Goadrich
2006The support vector decomposition machine.
Francisco Pereira, Geoffrey J. Gordon
2006The uniqueness of a good optimum for K-means.
Marina Meila
2006Topic modeling: beyond bag-of-words.
Hanna M. Wallach
2006Totally corrective boosting algorithms that maximize the margin.
Manfred K. Warmuth, Jun Liao, Gunnar Rätsch
2006Trading convexity for scalability.
Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou
2006Two-dimensional solution path for support vector regression.
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
2006Using inaccurate models in reinforcement learning.
Pieter Abbeel, Morgan Quigley, Andrew Y. Ng
2006Using query-specific variance estimates to combine Bayesian classifiers.
Chi-Hoon Lee, Russell Greiner, Shaojun Wang