AISTATS A

58 papers

YearTitle / Authors
2005A Graphical Model for Simultaneous Partitioning and Labeling.
Philip J. Cowans, Martin Szummer
2005A Uniform Convergence Bound for the Area Under the ROC Curve.
Shivani Agarwal, Sariel Har-Peled, Dan Roth
2005Active Learning for Parzen Window Classifier.
Olivier Chapelle
2005An Expectation Maximization Algorithm for Inferring Offset-Normal Shape Distributions.
Max Welling
2005Approximate Inference for Infinite Contingent Bayesian Networks.
Brian Milch, Bhaskara Marthi, David A. Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov
2005Approximations with Reweighted Generalized Belief Propagation.
Wim Wiegerinck
2005Bayesian Conditional Random Fields.
Yuan (Alan) Qi, Martin Szummer, Tom Minka
2005Convergent tree-reweighted message passing for energy minimization.
Vladimir Kolmogorov
2005Defensive Forecasting.
Vladimir Vovk, Akimichi Takemura, Glenn Shafer
2005Deformable Spectrograms.
Manuel Reyes-Gomez, Nebojsa Jojic, Daniel P. W. Ellis
2005Dirichlet Enhanced Latent Semantic Analysis.
Kai Yu, Shipeng Yu, Volker Tresp
2005Distributed Latent Variable Models of Lexical Co-occurrences.
John Blitzer, Amir Globerson, Fernando Pereira
2005Efficient Gradient Computation for Conditional Gaussian Models.
Bo Thiesson, Christopher Meek
2005Efficient Non-Parametric Function Induction in Semi-Supervised Learning.
Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
2005Estimating Class Membership Probabilities using Classifier Learners.
John Langford, Bianca Zadrozny
2005Fast Non-Parametric Bayesian Inference on Infinite Trees.
Marcus Hutter
2005Fast maximum a-posteriori inference on Monte Carlo state spaces.
Mike Klaas, Dustin Lang, Nando de Freitas
2005FastMap, MetricMap, and Landmark MDS are all Nystrom Algorithms.
John Platt
2005Focused Inference.
Rómer Rosales, Tommi S. Jaakkola
2005Gaussian Quadrature Based Expectation Propagation.
Onno Zoeter, Tom Heskes
2005Generative Model for Layers of Appearance and Deformation.
Anitha Kannan, Nebojsa Jojic, Brendan J. Frey
2005Greedy Spectral Embedding.
Marie Ouimet, Yoshua Bengio
2005Hierarchical Probabilistic Neural Network Language Model.
Frederic Morin, Yoshua Bengio
2005Hilbertian Metrics and Positive Definite Kernels on Probability Measures.
Matthias Hein, Olivier Bousquet
2005Inadequacy of interval estimates corresponding to variational Bayesian approximations.
Bo Wang, D. M. Titterington
2005Instrumental variable tests for Directed Acyclic Graph Models.
Manabu Kuroki, Zhihong Cai
2005Kernel Constrained Covariance for Dependence Measurement.
Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos K. Logothetis
2005Kernel Methods for Missing Variables.
Alexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann
2005Learning Bayesian Network Models from Incomplete Data using Importance Sampling.
Carsten Riggelsen, Ad Feelders
2005Learning Causally Linked Markov Random Fields.
Geoffrey E. Hinton, Simon Osindero, Kejie Bao
2005Learning in Markov Random Fields with Contrastive Free Energies.
Max Welling, Charles Sutton
2005Learning spectral graph segmentation.
Timothée Cour, Nicolas Gogin, Jianbo Shi
2005Loss Functions for Discriminative Training of Energy-Based Models.
Yann LeCun, Fu Jie Huang
2005Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization.
Kilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul
2005OOBN for Forensic Identification through Searching a DNA profiles' Database.
David Cavallini, Fabio Corradi
2005On Contrastive Divergence Learning.
Miguel Á. Carreira-Perpiñán, Geoffrey E. Hinton
2005On Manifold Regularization.
Misha Belkin, Partha Niyogi, Vikas Sindhwani
2005On the Behavior of MDL Denoising.
Teemu Roos, Petri Myllymäki, Henry Tirri
2005On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers.
Francis R. Bach, David Heckerman, Eric Horvitz
2005Online (and Offline) on an Even Tighter Budget.
Jason Weston, Antoine Bordes, Léon Bottou
2005Poisson-Networks: A Model for Structured Poisson Processes.
Shyamsundar Rajaram, Thore Graepel, Ralf Herbrich
2005Probabilistic Soft Interventions in Conditional Gaussian Networks.
Florian Markowetz, Steffen Grossmann, Rainer Spang
2005Probability and Statistics in the Law.
A. Philip Dawid
2005Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, AISTATS 2005, Bridgetown, Barbados, January 6-8, 2005
Robert G. Cowell, Zoubin Ghahramani
2005Recursive Autonomy Identification for Bayesian Network Structure Learning.
Raanan Yehezkel, Boaz Lerner
2005Regularized spectral learning.
Marina Meila, Susan M. Shortreed, Liang Xu
2005Restricted concentration models - graphical Gaussian models with concentration parameters restricted to being equal.
Søren Højsgaard, Steffen L. Lauritzen
2005Restructuring Dynamic Causal Systems in Equilibrium.
Denver Dash
2005Robust Higher Order Statistics.
Max Welling
2005Semi-Supervised Classification by Low Density Separation.
Olivier Chapelle, Alexander Zien
2005Semiparametric latent factor models.
Yee Whye Teh, Matthias W. Seeger, Michael I. Jordan
2005Semisupervised alignment of manifolds.
Jihun Ham, Daniel D. Lee, Lawrence K. Saul
2005Streaming Feature Selection using IIC.
Lyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine
2005Structured Variational Inference Procedures and their Realizations.
Dan Geiger, Christopher Meek
2005Toward Question-Asking Machines: The Logic of Questions and the Inquiry Calculus.
Kevin H. Knuth
2005Unsupervised Learning with Non-Ignorable Missing Data.
Benjamin M. Marlin, Sam T. Roweis, Richard S. Zemel
2005Variational Speech Separation of More Sources than Mixtures.
Steven J. Rennie, Kannan Achan, Brendan J. Frey, Parham Aarabi
2005Very Large SVM Training using Core Vector Machines.
Ivor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung