- 2005
- Matthias Hein, Olivier Bousquet:
Hilbertian Metrics and Positive Definite Kernels on Probability Measures. AISTATS 2005: 136-143 - Shivani Agarwal, Sariel Har-Peled
, Dan Roth:
A Uniform Convergence Bound for the Area Under the ROC Curve. AISTATS 2005: 1-8 - Bo Wang, D. M. Titterington:
Inadequacy of interval estimates corresponding to variational Bayesian approximations. AISTATS 2005: 373-380 - Francis R. Bach, David Heckerman, Eric Horvitz:
On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers. AISTATS 2005: 9-16 - Misha Belkin, Partha Niyogi, Vikas Sindhwani:
On Manifold Regularization. AISTATS 2005: 17-24 - John Blitzer, Amir Globerson, Fernando Pereira:
Distributed Latent Variable Models of Lexical Co-occurrences. AISTATS 2005: 25-32 - Miguel Á. Carreira-Perpiñán, Geoffrey E. Hinton:
On Contrastive Divergence Learning. AISTATS 2005: 33-40 - David Cavallini, Fabio Corradi:
OOBN for Forensic Identification through Searching a DNA profiles' Database. AISTATS 2005: 41-48 - Olivier Chapelle:
Active Learning for Parzen Window Classifier. AISTATS 2005: 49-56 - Olivier Chapelle, Alexander Zien:
Semi-Supervised Classification by Low Density Separation. AISTATS 2005: 57-64 - Timothée Cour, Nicolas Gogin, Jianbo Shi:
Learning spectral graph segmentation. AISTATS 2005: 65-72 - Philip J. Cowans, Martin Szummer:
A Graphical Model for Simultaneous Partitioning and Labeling. AISTATS 2005: 73-80 - Denver Dash:
Restructuring Dynamic Causal Systems in Equilibrium. AISTATS 2005: 81-88 - A. Philip Dawid:
Probability and Statistics in the Law. AISTATS 2005: 89-95 - Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux:
Efficient Non-Parametric Function Induction in Semi-Supervised Learning. AISTATS 2005: 96-103 - Dan Geiger, Christopher Meek:
Structured Variational Inference Procedures and their Realizations. AISTATS 2005: 104-111 - Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos K. Logothetis:
Kernel Constrained Covariance for Dependence Measurement. AISTATS 2005: 112-119 - Jihun Ham, Daniel D. Lee, Lawrence K. Saul:
Semisupervised alignment of manifolds. AISTATS 2005: 120-127 - Geoffrey E. Hinton, Simon Osindero, Kejie Bao:
Learning Causally Linked Markov Random Fields. AISTATS 2005: 128-135 - Søren Højsgaard, Steffen L. Lauritzen:
Restricted concentration models - graphical Gaussian models with concentration parameters restricted to being equal. AISTATS 2005: 152-157 - Marcus Hutter:
Fast Non-Parametric Bayesian Inference on Infinite Trees. AISTATS 2005: 144-151 - Anitha Kannan, Nebojsa Jojic, Brendan J. Frey:
Generative Model for Layers of Appearance and Deformation. AISTATS 2005: 166-173 - Mike Klaas, Dustin Lang, Nando de Freitas:
Fast maximum a-posteriori inference on Monte Carlo state spaces. AISTATS 2005: 158-165 - Kevin H. Knuth:
Toward Question-Asking Machines: The Logic of Questions and the Inquiry Calculus. AISTATS 2005: 174-180 - Vladimir Kolmogorov:
Convergent tree-reweighted message passing for energy minimization. AISTATS 2005: 182-189 - Manabu Kuroki, Zhihong Cai:
Instrumental variable tests for Directed Acyclic Graph Models. AISTATS 2005: 190-197 - John Langford, Bianca Zadrozny:
Estimating Class Membership Probabilities using Classifier Learners. AISTATS 2005: 198-205 - Yann LeCun, Fu Jie Huang:
Loss Functions for Discriminative Training of Energy-Based Models. AISTATS 2005: 206-213 - Florian Markowetz, Steffen Grossmann, Rainer Spang:
Probabilistic Soft Interventions in Conditional Gaussian Networks. AISTATS 2005: 214-221 - Benjamin M. Marlin, Sam T. Roweis, Richard S. Zemel:
Unsupervised Learning with Non-Ignorable Missing Data. AISTATS 2005: 222-229
