Table of Contents

• A Uniform Convergence Bound for the Area Under the ROC CurveShivani Agarwal 0001, Sariel Har-Peled, Dan Roth. 1-8 [doi]
• On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning ClassifiersFrancis R. Bach, David Heckerman, Eric Horvitz. 9-16 [doi]
• On Manifold RegularizationMisha Belkin, Partha Niyogi, Vikas Sindhwani. 17-24 [doi]
• Distributed Latent Variable Models of Lexical Co-occurrencesJohn Blitzer, Amir Globerson, Fernando Pereira 0003. 25-32 [doi]
• On Contrastive Divergence LearningMiguel Á. Carreira-Perpiñán, Geoffrey Hinton. 33-40 [doi]
• OOBN for Forensic Identification through Searching a DNA profiles' DatabaseDavid Cavallini, Fabio Corradi. 41-48 [doi]
• Active Learning for Parzen Window ClassifierOlivier Chapelle. 49-56 [doi]
• Semi-Supervised Classification by Low Density SeparationOlivier Chapelle, Alexander Zien. 57-64 [doi]
• Learning spectral graph segmentationTimothée Cour, Nicolas Gogin, Jianbo Shi. 65-72 [doi]
• A Graphical Model for Simultaneous Partitioning and LabelingPhilip J. Cowans, Martin Szummer. 73-80 [doi]
• Restructuring Dynamic Causal Systems in EquilibriumDenver Dash. 81-88 [doi]
• Probability and Statistics in the LawA. Philip Dawid. 89-95 [doi]
• Efficient Non-Parametric Function Induction in Semi-Supervised LearningOlivier Delalleau, Yoshua Bengio, Nicolas Le Roux. 96-103 [doi]
• Structured Variational Inference Procedures and their RealizationsDan Geiger, Christopher Meek. 104-111 [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. 112-119 [doi]
• Semisupervised alignment of manifoldsJihun Ham, Daniel D. Lee, Lawrence K. Saul. 120-127 [doi]
• Learning Causally Linked Markov Random FieldsGeoffrey E. Hinton, Simon Osindero, Kejie Bao. 128-135 [doi]
• Hilbertian Metrics and Positive Definite Kernels on Probability MeasuresMatthias Hein 0001, Olivier Bousquet. 136-143 [doi]
• Fast Non-Parametric Bayesian Inference on Infinite TreesMarcus Hutter. 144-151 [doi]
• Restricted concentration models - graphical Gaussian models with concentration parameters restricted to being equalSøren Højsgaard, Steffen L. Lauritzen. 152-157 [doi]
• Fast maximum a-posteriori inference on Monte Carlo state spacesMike Klaas, Dustin Lang, Nando de Freitas. 158-165 [doi]
• Generative Model for Layers of Appearance and DeformationAnitha Kannan, Nebojsa Jojic, Brendan J. Frey. 166-173 [doi]
• Toward Question-Asking Machines: The Logic of Questions and the Inquiry CalculusKevin Knuth. 174-180 [doi]
• Convergent tree-reweighted message passing for energy minimizationVladimir Kolmogorov. 182-189 [doi]
• Instrumental variable tests for Directed Acyclic Graph ModelsManabu Kuroki, Zhihong Cai. 190-197 [doi]
• Estimating Class Membership Probabilities using Classifier LearnersJohn Langford, Bianca Zadrozny. 198-205 [doi]
• Loss Functions for Discriminative Training of Energy-Based ModelsYann LeCun, Fu Jie Huang. 206-213 [doi]
• Probabilistic Soft Interventions in Conditional Gaussian NetworksFlorian Markowetz, Steffen Grossmann, Rainer Spang. 214-221 [doi]
• Unsupervised Learning with Non-Ignorable Missing DataBenjamin M. Marlin, Sam T. Roweis, Richard S. Zemel. 222-229 [doi]
• Regularized spectral learningMarina Meila, Susan M. Shortreed, Liang Xu. 230-237 [doi]
• Approximate Inference for Infinite Contingent Bayesian NetworksBrian Milch, Bhaskara Marthi, David Sontag, Stuart J. Russell, Daniel L. Ong, Andrey Kolobov. 238-245 [doi]
• Hierarchical Probabilistic Neural Network Language ModelFrederic Morin, Yoshua Bengio. 246-252 [doi]
• Greedy Spectral EmbeddingMarie Ouimet, Yoshua Bengio. 253-260 [doi]
• FastMap, MetricMap, and Landmark MDS are all Nystrom AlgorithmsJohn Platt. 261-268 [doi]
• Bayesian Conditional Random FieldsYuan (Alan) Qi, Martin Szummer, Tom Minka. 269-276 [doi]
• Poisson-Networks: A Model for Structured Poisson ProcessesShyamsundar Rajaram, Thore Graepel, Ralf Herbrich. 277-284 [doi]
• Deformable SpectrogramsManuel Reyes-Gomez, Nebojsa Jojic, Daniel P. W. Ellis. 285-292 [doi]
• Variational Speech Separation of More Sources than MixturesSteven J. Rennie, Kannan Achan, Brendan J. Frey, Parham Aarabi. 293-300 [doi]
• Learning Bayesian Network Models from Incomplete Data using Importance SamplingCarsten Riggelsen, Ad Feelders. 301-308 [doi]
• On the Behavior of MDL DenoisingTeemu Roos, Petri Myllymäki, Henry Tirri. 309-316 [doi]
• Focused InferenceRómer Rosales, Tommi Jaakkola. 317-324 [doi]
• Kernel Methods for Missing VariablesAlexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann. 325-332 [doi]
• Semiparametric latent factor modelsYee Whye Teh, Matthias Seeger, Michael I. Jordan. 333-340 [doi]
• Efficient Gradient Computation for Conditional Gaussian ModelsBo Thiesson, Christopher Meek. 341-348 [doi]
• Very Large SVM Training using Core Vector MachinesIvor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung. 349-356 [doi]
• Streaming Feature Selection using IICLyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine. 357-364 [doi]
• Defensive ForecastingVladimir Vovk, Akimichi Takemura, Glenn Shafer. 365-372 [doi]
• Inadequacy of interval estimates corresponding to variational Bayesian approximationsBo Wang 0002, D. M. Titterington. 373-380 [doi]
• Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix FactorizationKilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul. 381-388 [doi]
• An Expectation Maximization Algorithm for Inferring Offset-Normal Shape DistributionsMax Welling. 389-396 [doi]
• Learning in Markov Random Fields with Contrastive Free EnergiesMax Welling, Charles A. Sutton. 397-404 [doi]
• Robust Higher Order StatisticsMax Welling. 405-412 [doi]
• Online (and Offline) on an Even Tighter BudgetJason Weston, Antoine Bordes, Léon Bottou. 413-420 [doi]
• Approximations with Reweighted Generalized Belief PropagationWim Wiegerinck. 421-428 [doi]
• Recursive Autonomy Identification for Bayesian Network Structure LearningRaanan Yehezkel, Boaz Lerner. 429-436 [doi]
• Dirichlet Enhanced Latent Semantic AnalysisKai Yu, Shipeng Yu, Volker Tresp. 437-444 [doi]
• Gaussian Quadrature Based Expectation PropagationOnno Zoeter, Tom Heskes. 445-452 [doi]