- Marina Meila, Susan M. Shortreed, Liang Xu:
Regularized spectral learning. AISTATS 2005: 230-237 - Brian Milch, Bhaskara Marthi, David A. Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov:
Approximate Inference for Infinite Contingent Bayesian Networks. AISTATS 2005: 238-245 - Frederic Morin, Yoshua Bengio:
Hierarchical Probabilistic Neural Network Language Model. AISTATS 2005: 246-252 - Marie Ouimet, Yoshua Bengio:
Greedy Spectral Embedding. AISTATS 2005: 253-260 - John Platt:
FastMap, MetricMap, and Landmark MDS are all Nystrom Algorithms. AISTATS 2005: 261-268 - Yuan (Alan) Qi, Martin Szummer, Tom Minka:
Bayesian Conditional Random Fields. AISTATS 2005: 269-276 - Shyamsundar Rajaram, Thore Graepel, Ralf Herbrich:
Poisson-Networks: A Model for Structured Poisson Processes. AISTATS 2005: 277-284 - Steven J. Rennie, Kannan Achan, Brendan J. Frey, Parham Aarabi:
Variational Speech Separation of More Sources than Mixtures. AISTATS 2005: 293-300 - Manuel Reyes-Gomez, Nebojsa Jojic, Daniel P. W. Ellis:
Deformable Spectrograms. AISTATS 2005: 285-292 - Carsten Riggelsen, Ad Feelders:
Learning Bayesian Network Models from Incomplete Data using Importance Sampling. AISTATS 2005: 301-308 - Teemu Roos, Petri Myllymäki, Henry Tirri:
On the Behavior of MDL Denoising. AISTATS 2005: 309-316 - Rómer Rosales, Tommi S. Jaakkola:
Focused Inference. AISTATS 2005: 317-324 - Alexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann:
Kernel Methods for Missing Variables. AISTATS 2005: 325-332 - Yee Whye Teh, Matthias W. Seeger, Michael I. Jordan:
Semiparametric latent factor models. AISTATS 2005: 333-340 - Bo Thiesson, Christopher Meek:
Efficient Gradient Computation for Conditional Gaussian Models. AISTATS 2005: 341-348 - Ivor W. Tsang
, James Tin-Yau Kwok, Pak-Ming Cheung:
Very Large SVM Training using Core Vector Machines. AISTATS 2005: 349-356 - Lyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine:
Streaming Feature Selection using IIC. AISTATS 2005: 357-364 - Vladimir Vovk, Akimichi Takemura, Glenn Shafer:
Defensive Forecasting. AISTATS 2005: 365-372 - Kilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul:
Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization. AISTATS 2005: 381-388 - Max Welling:
An Expectation Maximization Algorithm for Inferring Offset-Normal Shape Distributions. AISTATS 2005: 389-396 - Max Welling:
Robust Higher Order Statistics. AISTATS 2005: 405-412 - Max Welling, Charles Sutton:
Learning in Markov Random Fields with Contrastive Free Energies. AISTATS 2005: 397-404 - Jason Weston, Antoine Bordes, Léon Bottou:
Online (and Offline) on an Even Tighter Budget. AISTATS 2005: 413-420 - Wim Wiegerinck:
Approximations with Reweighted Generalized Belief Propagation. AISTATS 2005: 421-428 - Raanan Yehezkel, Boaz Lerner:
Recursive Autonomy Identification for Bayesian Network Structure Learning. AISTATS 2005: 429-436 - Kai Yu, Shipeng Yu, Volker Tresp:
Dirichlet Enhanced Latent Semantic Analysis. AISTATS 2005: 437-444 - Onno Zoeter, Tom Heskes:
Gaussian Quadrature Based Expectation Propagation. AISTATS 2005: 445-452 - Robert G. Cowell, Zoubin Ghahramani:
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, AISTATS 2005, Bridgetown, Barbados, January 6-8, 2005. Society for Artificial Intelligence and Statistics 2005 [contents]
