AISTATS A

86 papers

YearTitle / Authors
2009A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation.
Frank D. Wood, Yee Whye Teh
2009A New Perspective for Information Theoretic Feature Selection.
Gavin Brown
2009A kernel method for unsupervised structured network inference.
Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten M. Borgwardt
2009Active Learning as Non-Convex Optimization.
Andrew Guillory, Erick Chastain, Jeff A. Bilmes
2009Active Sensing.
Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, R. Bharat Rao
2009An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward.
Matthew Hoffman, Nando de Freitas, Arnaud Doucet, Jan Peters
2009An Information Geometry Approach for Distance Metric Learning.
Shijun Wang, Rong Jin
2009Choosing a Variable to Clamp.
Frederik Eaton, Zoubin Ghahramani
2009Chromatic PAC-Bayes Bounds for Non-IID Data.
Liva Ralaivola, Marie Szafranski, Guillaume Stempfel
2009Clusterability: A Theoretical Study.
Margareta Ackerman, Shai Ben-David
2009Coherence Functions for Multicategory Margin-based Classification Methods.
Zhihua Zhang, Michael I. Jordan, Wu-Jun Li, Dit-Yan Yeung
2009Convex Perturbations for Scalable Semidefinite Programming.
Brian Kulis, Suvrit Sra, Inderjit S. Dhillon
2009Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings.
Minyoung Kim, Vladimir Pavlovic
2009Data Biased Robust Counter Strategies.
Michael Johanson, Michael H. Bowling
2009Deep Boltzmann Machines.
Ruslan Salakhutdinov, Geoffrey E. Hinton
2009Deep Learning using Robust Interdependent Codes.
Hugo Larochelle, Dumitru Erhan, Pascal Vincent
2009Distilled sensing: selective sampling for sparse signal recovery.
Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak
2009Dual Temporal Difference Learning.
Min Yang, Yuxi Li, Dale Schuurmans
2009Efficient graphlet kernels for large graph comparison.
Nino Shervashidze, S. V. N. Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten M. Borgwardt
2009Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming.
Héctor Corrada Bravo, Stephen J. Wright, Kevin H. Eng, Sündüz Keles, Grace Wahba
2009Estimation Consistency of the Group Lasso and its Applications.
Han Liu, Jian Zhang
2009Exact and Approximate Sampling by Systematic Stochastic Search.
Vikash Mansinghka, Daniel M. Roy, Eric Jonas, Joshua B. Tenenbaum
2009Exploiting Probabilistic Independence for Permutations.
Jonathan Huang, Carlos Guestrin, Xiaoye Jiang, Leonidas J. Guibas
2009Factorial Mixture of Gaussians and the Marginal Independence Model.
Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani
2009Gaussian Margin Machines.
Koby Crammer, Mehryar Mohri, Fernando Pereira
2009Group Nonnegative Matrix Factorization for EEG Classification.
Hyekyoung Lee, Seungjin Choi
2009Handling Sparsity via the Horseshoe.
Carlos M. Carvalho, Nicholas G. Polson, James G. Scott
2009Hash Kernels.
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan
2009Infinite Hierarchical Hidden Markov Models.
Katherine A. Heller, Yee Whye Teh, Dilan Görür
2009Inverse Optimal Heuristic Control for Imitation Learning.
Nathan D. Ratliff, Brian D. Ziebart, Kevin M. Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, Siddhartha S. Srinivasa
2009Kernel Learning by Unconstrained Optimization.
Fuxin Li, Yun-Shan Fu, Yu-Hong Dai, Cristian Sminchisescu, Jue Wang
2009Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression.
Nicole Krämer, Masashi Sugiyama, Mikio L. Braun
2009Large-Margin Structured Prediction via Linear Programming.
Zhuoran Wang, John Shawe-Taylor
2009Latent Force Models.
Mauricio A. Álvarez, David Luengo, Neil D. Lawrence
2009Latent Variable Models for Dimensionality Reduction.
Zhihua Zhang, Michael I. Jordan
2009Latent Wishart Processes for Relational Kernel Learning.
Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung
2009Learning Exercise Policies for American Options.
Yuxi Li, Csaba Szepesvári, Dale Schuurmans
2009Learning Low Density Separators.
Shai Ben-David, Tyler Lu, Dávid Pál, Miroslava Sotáková
2009Learning Sparse Markov Network Structure via Ensemble-of-Trees Models.
Yuanqing Lin, Shenghuo Zhu, Daniel D. Lee, Ben Taskar
2009Learning Thin Junction Trees via Graph Cuts.
Dafna Shahaf, Carlos Guestrin
2009Learning a Parametric Embedding by Preserving Local Structure.
Laurens van der Maaten
2009Learning the Switching Rate by Discretising Bernoulli Sources Online.
Steven de Rooij, Tim van Erven
2009Locally Minimax Optimal Predictive Modeling with Bayesian Networks.
Tomi Silander, Teemu Roos, Petri Myllymäki
2009MCMC Methods for Bayesian Mixtures of Copulas.
Ricardo Bezerra de Andrade e Silva, Robert B. Gramacy
2009Markov Topic Models.
Chong Wang, Bo Thiesson, Christopher Meek, David M. Blei
2009Matching Pursuit Kernel Fisher Discriminant Analysis.
Tom Diethe, Zakria Hussain, David R. Hardoon, John Shawe-Taylor
2009Maximum Entropy Density Estimation with Incomplete Presence-Only Data.
Bert Huang, Ansaf Salleb-Aouissi
2009Multi-Manifold Semi-Supervised Learning.
Andrew B. Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, Robert D. Nowak
2009Network Completion and Survey Sampling.
Steve Hanneke, Eric P. Xing
2009Non-Negative Semi-Supervised Learning.
Changhu Wang, Shuicheng Yan, Lei Zhang, HongJiang Zhang
2009Novelty detection: Unlabeled data definitely help.
Clayton Scott, Gilles Blanchard
2009On Partitioning Rules for Bipartite Ranking.
Stéphan Clémençon, Nicolas Vayatis
2009Online Inference of Topics with Latent Dirichlet Allocation.
Kevin Robert Canini, Lei Shi, Thomas L. Griffiths
2009Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm.
Mark Schmidt, Ewout van den Berg, Michael P. Friedlander, Kevin P. Murphy
2009PAC-Bayes Analysis Of Maximum Entropy Classification.
John Shawe-Taylor, David R. Hardoon
2009PAC-Bayesian Generalization Bound for Density Estimation with Application to Co-clustering.
Yevgeny Seldin, Naftali Tishby
2009Particle Belief Propagation.
Alexander Ihler, David A. McAllester
2009Preface.
David A. Van Dyk, Max Welling
2009Probabilistic Models for Incomplete Multi-dimensional Arrays.
Wei Chu, Zoubin Ghahramani
2009Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, AISTATS 2009, Clearwater Beach, Florida, USA, April 16-18, 2009
David A. Van Dyk, Max Welling
2009Relational Topic Models for Document Networks.
Jonathan D. Chang, David M. Blei
2009Relative Novelty Detection.
Alexander J. Smola, Le Song, Choon Hui Teo
2009Residual Splash for Optimally Parallelizing Belief Propagation.
Joseph Gonzalez, Yucheng Low, Carlos Guestrin
2009Reversible Jump MCMC for Non-Negative Matrix Factorization.
Mingjun Zhong, Mark A. Girolami
2009Sampling Techniques for the Nystrom Method.
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
2009Semi-Supervised Affinity Propagation with Instance-Level Constraints.
Inmar E. Givoni, Brendan J. Frey
2009Sequential Learning of Classifiers for Structured Prediction Problems.
Dan Roth, Kevin Small, Ivan Titov
2009Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards.
Varun Kanade, H. Brendan McMahan, Brent Bryan
2009Spanning Tree Approximations for Conditional Random Fields.
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhmann
2009Sparse Probabilistic Principal Component Analysis.
Yue Guan, Jennifer G. Dy
2009Speed and Sparsity of Regularized Boosting.
Yongxin Taylor Xi, Zhen James Xiang, Peter J. Ramadge, Robert E. Schapire
2009Statistical and Computational Tradeoffs in Stochastic Composite Likelihood.
Joshua V. Dillon, Guy Lebanon
2009Structure Identification by Optimized Interventions.
Alberto Giovanni Busetto, Joachim M. Buhmann
2009Supervised Spectral Latent Variable Models.
Liefeng Bo, Cristian Sminchisescu
2009The Block Diagonal Infinite Hidden Markov Model.
Thomas S. Stepleton, Zoubin Ghahramani, Geoffrey J. Gordon, Tai Sing Lee
2009The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training.
Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent
2009Tighter and Convex Maximum Margin Clustering.
Yufeng Li, Ivor W. Tsang, James Tin-Yau Kwok, Zhi-Hua Zhou
2009Tractable Bayesian Inference of Time-Series Dependence Structure.
Michael Siracusa, John W. Fisher III
2009Tractable Search for Learning Exponential Models of Rankings.
Bhushan Mandhani, Marina Meila
2009Tree Block Coordinate Descent for MAP in Graphical Models.
David A. Sontag, Tommi S. Jaakkola
2009Tree-Based Inference for Dirichlet Process Mixtures.
Yang Xu, Katherine A. Heller, Zoubin Ghahramani
2009Variable Metric Stochastic Approximation Theory.
Peter Sunehag, Jochen Trumpf, S. V. N. Vishwanathan, Nicol N. Schraudolph
2009Variational Bridge Regression.
Artin Armagan
2009Variational Inference for the Indian Buffet Process.
Finale Doshi, Kurt Miller, Jurgen Van Gael, Yee Whye Teh
2009Variational Learning of Inducing Variables in Sparse Gaussian Processes.
Michalis K. Titsias
2009Visualization Databases for the Analysis of Large Complex Datasets.
Saptarshi Guha, Paul Kidwell, Ryan Hafen, William S. Cleveland