AISTATS 2010

125 papers

Graphical Gaussian modelling of multivariate time series with latent variables

Michael Eichler

Combining Experiments to Discover Linear Cyclic Models with Latent Variables

Frederick Eberhardt, Patrik Hoyer, Richard Scheines

Neural conditional random fields

Trinh–Minh–Tri Do, Thierry Artières

Nonparametric Bayesian Matrix Factorization by Power-EP

Nan Ding, Yuan Qi, Rongjing Xiang, Ian Molloy, Ninghui Li

Bayesian variable order Markov models

Christos Dimitrakakis

Feature Selection using Multiple Streams

Paramveer Dhillon, Dean Foster, Lyle Ungar

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines

Guillaume Desjardins, Aaron Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau

Multiclass-Multilabel Classification with More Classes than Examples

Ofer Dekel, Ohad Shamir

Impossibility Theorems for Domain Adaptation

Shai Ben David, Tyler Lu, Teresa Luu, Dávid Pál

Improving posterior marginal approximations in latent Gaussian models

Botond Cseke, Tom Heskes

On the Impact of Kernel Approximation on Learning Accuracy

Corinna Cortes, Mehryar Mohri, Ameet Talwalkar

Mass Fatality Incident Identification based on nuclear DNA evidence

Fabio Corradi

Parametric Herding

Yutian Chen, Max Welling

Focused Belief Propagation for Query-Specific Inference

Anton Chechetka, Carlos Guestrin

Why are DBNs sparse?

Shaunak Chatterjee, Stuart Russell

Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs

Hei Chan, manabu kuroki

Towards Understanding Situated Natural Language

Antoine Bordes, Nicolas Usunier, Ronan Collobert, Jason Weston

Kernel Partial Least Squares is Universally Consistent

Gilles Blanchard, Nicole Krämer

Half Transductive Ranking

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes

Deterministic Bayesian inference for the $p*$ model

Haakon Austad, Nial Friel

Learning with Blocks: Composite Likelihood and Contrastive Divergence

Arthur Asuncion, Qiang Liu, Alexander Ihler, Padhraic Smyth

Efficient Multioutput Gaussian Processes through Variational Inducing Kernels

Mauricio Alvarez, David Luengo, Michalis Titsias, Neil D. Lawrence

Multitask Learning for Brain-Computer Interfaces

Morteza Alamgir, Moritz Grosse–Wentrup, Yasemin Altun

Optimal Allocation Strategies for the Dark Pool Problem

Alekh Agarwal, Peter Bartlett, Max Dama

Learning the Structure of Deep Sparse Graphical Models

Ryan P. Adams, Hanna Wallach, Zoubin Ghahramani