Table of Contents

• Generalized belief propagation for approximate inference in hybrid Bayesian networksTom Heskes, Onno Zoeter. [doi]
• Sequential Importance Sampling for Visual Tracking ReconsideredPéter Torma, Csaba Szepesvári. [doi]
• A Generalized Linear Model for Principal Component Analysis of Binary DataAndrew I. Schein, Lawrence K. Saul, Lyle H. Ungar. [doi]
• An Active Approach to Collaborative FilteringRichard S. Zemel, Craig Boutilier. [doi]
• Fast Marginal Likelihood Maximisation for Sparse Bayesian ModelsMichael E. Tipping, Anita C. Faul. [doi]
• Curve Clustering with Random Effects Regression MixturesScott Gaffney, Padhraic Smyth. [doi]
• On the Naive Bayes Model for Text CategorizationSusana Eyheramendy, David D. Lewis, David Madigan. [doi]
• Towards Principled Feature Selection: Relevancy, Filters and WrappersIoannis Tsamardinos, Constantin F. Aliferis. [doi]
• Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic SignalsIead Rezek, Stephen J. Roberts, Peter Sykacek. [doi]
• Learning Bayesian Networks From Dependency Networks: A Preliminary StudyGeoff Hulten, David Maxwell Chickering, David Heckerman. [doi]
• Efficient Computing of Stochastic ComplexityPetri Kontkanen, Wray L. Buntine, Petri Myllymäki, Jorma Rissanen, Henry Tirri. [doi]
• Super-resolution Enhancement of VideoChristopher M. Bishop, Andrew Blake, Bhaskara Marthi. [doi]
• Fast Robust Logistic Regression for Large Sparse Datasets with Binary OutputsPaul Komarek, Andrew W. Moore. [doi]
• Latent Maximum Entropy Approach for Semantic N-gram Language ModelingShaojun Wang, Dale Schuurmans, Fuchun Peng. [doi]
• Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matchingMartin J. Wainwright, Tommi Jaakkola, Alan S. Willsky. [doi]
• Expectation Maximization of Forward Decoding Kernel MachinesShantanu Chakrabartty, Gert Cauwenberghs. [doi]
• On Boosting and the Exponential LossAbraham J. Wyner. [doi]
• A Blessing of Dimensionality: Measure Concentration and Probabilistic InferencePinar Muyan, Nando de Freitas. [doi]
• Data centering in feature spaceMarina Meila. [doi]
• Planning by Probabilistic InferenceHagai Attias. [doi]
• The Sound of an Album Cover: A Probabilistic Approach to MultimediaEric Brochu, Nando de Freitas, Kejie Bao. [doi]
• A Bayesian Approach to Bergman's Minimal ModelKim E. Andersen, Malene Højbjerre. [doi]
• An object-oriented Bayesian network for estimating mutation ratesA. Philip Dawid. [doi]
• Combining Conjugate Direction Methods with Stochastic Approximation of GradientsNicol N. Schraudolph, Thore Graepel. [doi]
• The Joint Causal Effect in Linear Structural Equation Model and Its Application to Process AnalysisManabu Kuroki, Zhihong Cai. [doi]
• Clustering Markov States into Equivalence Classes using SVD and Heuristic Search AlgorithmsXianping Ge, Sridevi Parise, Padhraic Smyth. [doi]
• Refining Kernels for Regression and Uneven Classification ProblemsJaz S. Kandola, John Shawe-Taylor. [doi]
• Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction?Wray L. Buntine, Sami Perttu. [doi]
• Reduced Rank Approximations of Transition MatricesJuan Lin. [doi]
• Document Retrieval and Clustering: from Principal Component Analysis to Self-aggregation NetworksChris Ding. [doi]
• Fast Forward Selection to Speed Up Sparse Gaussian Process RegressionMatthias W. Seeger, Christopher K. I. Williams, Neil D. Lawrence. [doi]
• On Improving the Efficiency of the Iterative Proportional Fitting ProcedureYee Whye Teh, Max Welling. [doi]
• Rapid Evaluation of Multiple Density ModelsAlexander G. Gray, Andrew W. Moore. [doi]
• Solving Markov Random Fields using Semi Definite ProgrammingPhilip H. S. Torr. [doi]
• Model Averaging with Bayesian Network ClassifiersDenver Dash, Gregory F. Cooper. [doi]
• Quick Training of Probabilistic Neural Nets by Importance SamplingYoshua Bengio, Jean-Sébastien Senecal. [doi]
• Structured Variational Distributions in VIBESChristopher M. Bishop, John M. Winn. [doi]
• Real-time On-line Learning of Transformed Hidden Markov Models from VideoNemanja Petrovic, Nebojsa Jojic, Brendan J. Frey, Thomas S. Huang. [doi]
• On Retrieval Properties of Samples of Large CollectionsDavid Madigan, Yehuda Vardi, Ishay Weissman. [doi]
• Bayesian Inference in the Presence of DeterminismDavid Larkin, Rina Dechter. [doi]
• Bayesian Feature Weighting for Unsupervised Learning, with Application to Object RecognitionPaul Gustafson, Peter Carbonetto, Natalie Thompson, Nando de Freitas. [doi]
• Convex Invariance LearningTony Jebara. [doi]
• Discriminative Model Selection for Density ModelsBo Thiesson, Christopher Meek. [doi]
• A unifying theorem for spectral embedding and clusteringMatthew Brand, Kun Huang. [doi]