Frontmatter and Preface

Robert G. Cowell, Zoubin Ghahramani; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:i-vii

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A Uniform Convergence Bound for the Area Under the ROC Curve

Shivani Agarwal, Sariel Har-Peled, Dan Roth; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:1-8

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On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers

Francis Bach, David Heckerman, Eric Horvitz; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:9-16

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On Manifold Regularization

Misha Belkin, Partha Niyogi, Vikas Sindhwani; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:17-24

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Distributed Latent Variable Models of Lexical Co-occurrences

John Blitzer, Amir Globerson, Fernando Pereira; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:25-32

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On Contrastive Divergence Learning

Miguel Á. Carreira-Perpiñán, Geoffrey Hinton; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:33-40

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OOBN for Forensic Identification through Searching a DNA profiles’ Database

David Cavallini, Fabio Corradi; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:41-48

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Active Learning for Parzen Window Classifier

Olivier Chapelle; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:49-56

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Semi-Supervised Classification by Low Density Separation

Olivier Chapelle, Alexander Zien; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:57-64

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Learning spectral graph segmentation

Timothée Cour, Nicolas Gogin, Jianbo Shi; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:65-72

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A Graphical Model for Simultaneous Partitioning and Labeling

Philip J. Cowans, Martin Szummer; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:73-80

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Restructuring Dynamic Causal Systems in Equilibrium

Denver Dash; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:81-88

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Probability and Statistics in the Law

Philip Dawid; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:89-95

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Efficient Non-Parametric Function Induction in Semi-Supervised Learning

Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:96-103

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Structured Variational Inference Procedures and their Realizations

Dan Geiger, Chris Meek; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:104-111

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Kernel Constrained Covariance for Dependence Measurement

Arthur Gretton, Alexander Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos Logothetis; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:112-119

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Semisupervised alignment of manifolds

Jihun Ham, Daniel Lee, Lawrence Saul; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:120-127

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Learning Causally Linked Markov Random Fields

Geoffrey Hinton, Simon Osindero, Kejie Bao; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:128-135

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Hilbertian Metrics and Positive Definite Kernels on Probability Measures

Matthias Hein, Olivier Bousquet; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:136-143

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Fast Non-Parametric Bayesian Inference on Infinite Trees

Marcus Hutter; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:144-151

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Restricted concentration models – graphical Gaussian models with concentration parameters restricted to being equal

Søren Højsgaard, Steffen Lauritzen; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:152-157

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Fast maximum a-posteriori inference on Monte Carlo state spaces

Mike Klaas, Dustin Lang, Nando de Freitas; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:158-165

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Generative Model for Layers of Appearance and Deformation

Anitha Kannan, Nebojsa Jojic, Brendan Frey; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:166-173

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Toward Question-Asking Machines: The Logic of Questions and the Inquiry Calculus

Kevin Knuth; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:174-180

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Convergent tree-reweighted message passing for energy minimization

Vladimir Kolmogorov; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:182-189

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Instrumental variable tests for Directed Acyclic Graph Models

Manabu Kuroki, Zhihong Cai; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:190-197

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Estimating Class Membership Probabilities using Classifier Learners

John Langford, Bianca Zadrozny; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:198-205

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Loss Functions for Discriminative Training of Energy-Based Models

Yann LeCun, Fu Jie Huang; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:206-213

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Probabilistic Soft Interventions in Conditional Gaussian Networks

Florian Markowetz, Steffen Grossmann, Rainer Spang; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:214-221

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Unsupervised Learning with Non-Ignorable Missing Data

Benjamin M. Marlin, Sam T. Roweis, Richard S. Zemel; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:222-229

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Regularized spectral learning

Marina Meilă, Susan Shortreed, Liang Xu; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:230-237

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Approximate Inference for Infinite Contingent Bayesian Networks

Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:238-245

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Hierarchical Probabilistic Neural Network Language Model

Frederic Morin, Yoshua Bengio; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:246-252

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Greedy Spectral Embedding

Marie Ouimet, Yoshua Bengio; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:253-260

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FastMap, MetricMap, and Landmark MDS are all Nyström Algorithms

John Platt; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:261-268

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Bayesian Conditional Random Fields

Yuan Qi, Martin Szummer, Tom Minka; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:269-276

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Poisson-Networks: A Model for Structured Poisson Processes

Shyamsundar Rajaram, Thore Graepel, Ralf Herbrich; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:277-284

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Deformable Spectrograms

Manuel Reyes-Gomez, Nebojsa Jojic, Daniel Ellis; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:285-292

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Variational Speech Separation of More Sources than Mixtures

Steven J. Rennie, Kannan Achan, Brendan J. Frey, Parham Aarabi; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:293-300

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Learning Bayesian Network Models from Incomplete Data using Importance Sampling

Carsten Riggelsen, Ad Feelders; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:301-308

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On the Behavior of MDL Denoising

Teemu Roos, Petri Myllymäki, Henry Tirri; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:309-316

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Focused Inference

Romer Rosales, Tommi S. Jaakkola; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:317-324

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Kernel Methods for Missing Variables

Alex J. Smola, S. V. N. Vishwanathan, Thomas Hofmann; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:325-332

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Semiparametric latent factor models

Yee Whye Teh, Matthias Seeger, Michael I. Jordan; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:333-340

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Efficient Gradient Computation for Conditional Gaussian Models

Bo Thiesson, Chris Meek; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:341-348

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Very Large SVM Training using Core Vector Machines

Ivor Tsang, James Kwok, Pak-Ming Cheung; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:349-356

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Streaming Feature Selection using IIC

Lyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:357-364

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Defensive Forecasting

Vladimir Vovk, Akimichi Takemura, Glenn Shafer; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:365-372

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Inadequacy of interval estimates corresponding to variational Bayesian approximations

Bo Wang, D. M. Titterington; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:373-380

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Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization

Kilian Weinberger, Benjamin Packer, Lawrence Saul; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:381-388

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An Expectation Maximization Algorithm for Inferring Offset-Normal Shape Distributions

Max Welling; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:389-396

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Learning in Markov Random Fields with Contrastive Free Energies

Max Welling, Charles Sutton; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:397-404

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Robust Higher Order Statistics

Max Welling; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:405-412

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Online (and Offline) on an Even Tighter Budget

Jason Weston, Antoine Bordes, Leon Bottou; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:413-420

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Approximations with Reweighted Generalized Belief Propagation

Wim Wiegerinck; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:421-428

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Recursive Autonomy Identification for Bayesian Network Structure Learning

Raanan Yehezkel, Boaz Lerner; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:429-436

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Dirichlet Enhanced Latent Semantic Analysis

Kai Yu, Shipeng Yu, Volker Tresp; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:437-444

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Gaussian Quadrature Based Expectation Propagation

Onno Zoeter, Tom Heskes; Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, PMLR R5:445-452

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