Abstract is missing.
- Fast Non-Parametric Bayesian Inference on Infinite TreesMarcus Hutter. [doi]
- Inadequacy of interval estimates corresponding to variational Bayesian approximationsBo Wang 0002, D. M. Titterington. [doi]
- Kernel Methods for Missing VariablesAlexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann. [doi]
- Learning Bayesian Network Models from Incomplete Data using Importance SamplingCarsten Riggelsen, Ad Feelders. [doi]
- Semi-Supervised Classification by Low Density SeparationOlivier Chapelle, Alexander Zien. [doi]
- Unsupervised Learning with Non-Ignorable Missing DataBenjamin M. Marlin, Sam T. Roweis, Richard S. Zemel. [doi]
- A Uniform Convergence Bound for the Area Under the ROC CurveShivani Agarwal 0001, Sariel Har-Peled, Dan Roth. [doi]
- Loss Functions for Discriminative Training of Energy-Based ModelsYann LeCun, Fu Jie Huang. [doi]
- Convergent tree-reweighted message passing for energy minimizationVladimir Kolmogorov. [doi]
- Fast maximum a-posteriori inference on Monte Carlo state spacesMike Klaas, Dustin Lang, Nando de Freitas. [doi]
- FastMap, MetricMap, and Landmark MDS are all Nystrom AlgorithmsJohn Platt. [doi]
- Kernel Constrained Covariance for Dependence MeasurementArthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos K. Logothetis. [doi]
- Semiparametric latent factor modelsYee Whye Teh, Matthias Seeger, Michael I. Jordan. [doi]
- A Graphical Model for Simultaneous Partitioning and LabelingPhilip J. Cowans, Martin Szummer. [doi]
- Probability and Statistics in the LawA. Philip Dawid. [doi]
- Online (and Offline) on an Even Tighter BudgetJason Weston, Antoine Bordes, Léon Bottou. [doi]
- On Contrastive Divergence LearningMiguel Á. Carreira-Perpiñán, Geoffrey Hinton. [doi]
- Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix FactorizationKilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul. [doi]
- Instrumental variable tests for Directed Acyclic Graph ModelsManabu Kuroki, Zhihong Cai. [doi]
- Efficient Non-Parametric Function Induction in Semi-Supervised LearningOlivier Delalleau, Yoshua Bengio, Nicolas Le Roux. [doi]
- On Manifold RegularizationMisha Belkin, Partha Niyogi, Vikas Sindhwani. [doi]
- Approximations with Reweighted Generalized Belief PropagationWim Wiegerinck. [doi]
- Probabilistic Soft Interventions in Conditional Gaussian NetworksFlorian Markowetz, Steffen Grossmann, Rainer Spang. [doi]
- Generative Model for Layers of Appearance and DeformationAnitha Kannan, Nebojsa Jojic, Brendan J. Frey. [doi]
- Variational Speech Separation of More Sources than MixturesSteven J. Rennie, Kannan Achan, Brendan J. Frey, Parham Aarabi. [doi]
- Toward Question-Asking Machines: The Logic of Questions and the Inquiry CalculusKevin Knuth. [doi]
- Bayesian Conditional Random FieldsYuan (Alan) Qi, Martin Szummer, Tom Minka. [doi]
- Recursive Autonomy Identification for Bayesian Network Structure LearningRaanan Yehezkel, Boaz Lerner. [doi]
- OOBN for Forensic Identification through Searching a DNA profiles' DatabaseDavid Cavallini, Fabio Corradi. [doi]
- Learning in Markov Random Fields with Contrastive Free EnergiesMax Welling, Charles A. Sutton. [doi]
- On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning ClassifiersFrancis R. Bach, David Heckerman, Eric Horvitz. [doi]
- Efficient Gradient Computation for Conditional Gaussian ModelsBo Thiesson, Christopher Meek. [doi]
- Very Large SVM Training using Core Vector MachinesIvor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung. [doi]
- Deformable SpectrogramsManuel Reyes-Gomez, Nebojsa Jojic, Daniel P. W. Ellis. [doi]
- Regularized spectral learningMarina Meila, Susan M. Shortreed, Liang Xu. [doi]
- Restricted concentration models - graphical Gaussian models with concentration parameters restricted to being equalSøren Højsgaard, Steffen L. Lauritzen. [doi]
- On the Behavior of MDL DenoisingTeemu Roos, Petri Myllymäki, Henry Tirri. [doi]
- Hilbertian Metrics and Positive Definite Kernels on Probability MeasuresMatthias Hein 0001, Olivier Bousquet. [doi]
- Active Learning for Parzen Window ClassifierOlivier Chapelle. [doi]
- Approximate Inference for Infinite Contingent Bayesian NetworksBrian Milch, Bhaskara Marthi, David Sontag, Stuart J. Russell, Daniel L. Ong, Andrey Kolobov. [doi]
- Robust Higher Order StatisticsMax Welling. [doi]
- Greedy Spectral EmbeddingMarie Ouimet, Yoshua Bengio. [doi]
- Distributed Latent Variable Models of Lexical Co-occurrencesJohn Blitzer, Amir Globerson, Fernando Pereira 0003. [doi]
- Semisupervised alignment of manifoldsJihun Ham, Daniel D. Lee, Lawrence K. Saul. [doi]
- Poisson-Networks: A Model for Structured Poisson ProcessesShyamsundar Rajaram, Thore Graepel, Ralf Herbrich. [doi]
- An Expectation Maximization Algorithm for Inferring Offset-Normal Shape DistributionsMax Welling. [doi]
- Gaussian Quadrature Based Expectation PropagationOnno Zoeter, Tom Heskes. [doi]
- Hierarchical Probabilistic Neural Network Language ModelFrederic Morin, Yoshua Bengio. [doi]
- Estimating Class Membership Probabilities using Classifier LearnersJohn Langford, Bianca Zadrozny. [doi]
- Defensive ForecastingVladimir Vovk, Akimichi Takemura, Glenn Shafer. [doi]
- Focused InferenceRómer Rosales, Tommi Jaakkola. [doi]
- Restructuring Dynamic Causal Systems in EquilibriumDenver Dash. [doi]
- Structured Variational Inference Procedures and their RealizationsDan Geiger, Christopher Meek. [doi]
- Learning spectral graph segmentationTimothée Cour, Nicolas Gogin, Jianbo Shi. [doi]
- Learning Causally Linked Markov Random FieldsGeoffrey E. Hinton, Simon Osindero, Kejie Bao. [doi]
- Streaming Feature Selection using IICLyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine. [doi]
- Dirichlet Enhanced Latent Semantic AnalysisKai Yu, Shipeng Yu, Volker Tresp. [doi]