AISTATS Conference Schedule

Poster Session III, Saturday May 15

Contributed Posters

Reducing Label Complexity by Learning From Bags
S. Sabato, N. Srebro and N. Tishby [abs] [pdf]

Conditional Density Estimation via Least-Squares Density Ratio Estimation
M. Sugiyama, I. Takeuchi, T. Suzuki, T. Kanamori, H. Hachiya and D. Okanohara [abs] [pdf]

Convexity of Proper Composite Binary Losses
M. Reid and R. Williamson [abs] [pdf]

Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries
S. Guo and S. Sanner [abs] [pdf]

Unsupervised Aggregation for Classification Problems with Large Numbers of Categories
I. Titov, A. Klementiev, K. Small and D. Roth [abs] [pdf]

Contextual Multi-Armed Bandits
T. Lu, D. Pal and M. Pal [abs] [pdf] [supplementary]

A Potential-based Framework for Online Multi-class Learning with Partial Feedback
S. Wang, R. Jin and H. Valizadegan [abs] [pdf]

Regret Bounds for Gaussian Process Bandit Problems
S. Grünewälder, J. Audibert, M. Opper and J. Shawe–Taylor [abs] [pdf]

Active Sequential Learning with Tactile Feedback
H. Saal, J. Ting and S. Vijayakumar [abs] [pdf] [supplementary]

A highly efficient blocked Gibbs sampler reconstruction of multidimensional NMR spectra
J. Won Yoon, S. Wilson and K. Hun Mok [abs] [pdf]

Optimal Allocation Strategies for the Dark Pool Problem
A. Agarwal, P. Bartlett and M. Dama [abs] [pdf]

Multitask Learning for Brain-Computer Interfaces
M. Alamgir, M. Grosse–Wentrup and Y. Altun [abs] [pdf]

An Alternative Prior Process for Nonparametric Bayesian Clustering
H. Wallach, S. Jensen, L. Dicker and K. Heller [abs] [pdf] [supplementary]

Matrix-Variate Dirichlet Process Mixture Models
Z. Zhang, G. Dai and M. Jordan [abs] [pdf]

Dependent Indian Buffet Processes
S. Williamson, P. Orbanz and Z. Ghahramani [abs] [pdf]

Posterior distributions are computable from predictive distributions
C. Freer and D. Roy [abs] [pdf]

A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection
S. Pandolfi, F. Bartolucci and N. Friel [abs] [pdf]

Sequential Monte Carlo Samplers for Dirichlet Process Mixtures
Y. Ulker, B. Günsel and T. Cemgil [abs] [pdf]

Learning Bayesian Network Structure using LP Relaxations
T. Jaakkola, D. Sontag, A. Globerson and M. Meila [abs] [pdf]

Bayesian structure discovery in Bayesian networks with less space
P. Parviainen and M. Koivisto [abs] [pdf]

Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks
N. Slavov [abs] [pdf]

Simple Exponential Family PCA
J. Li and D. Tao [abs] [pdf]

Locally Linear Denoising on Image Manifolds
D. Gong, F. Sha and G. Medioni [abs] [pdf]

Supervised Dimension Reduction Using Bayesian Mixture Modeling
K. Mao, F. Liang and S. Mukherjee [abs] [pdf]

Hartigan's Method: k-means Clustering without Voronoi
M. Telgarsky and A. Vattani [abs] [pdf]

Towards Understanding Situated Natural Language
A. Bordes, N. Usunier, R. Collobert and J. Weston [abs] [pdf]

Discriminative Topic Segmentation of Text and Speech
M. Mohri, P. Moreno and E. Weinstein [abs] [pdf]

State-Space Inference and Learning with Gaussian Processes
R. Turner, M. Deisenroth and C. Rasmussen [abs] [pdf]

Model-Free Monte Carlo-like Policy Evaluation
R. Fonteneau, S. Murphy, L. Wehenkel and D. Ernst [abs] [pdf]

Variational methods for Reinforcement Learning
T. Furmston and D. Barber [abs] [pdf]

Efficient Learning of Deep Boltzmann Machines
R. Salakhutdinov and H. Larochelle [abs] [pdf]

Inductive Principles for Restricted Boltzmann Machine Learning
B. Marlin, K. Swersky, B. Chen and N. de Freitas [abs] [pdf]

Why Does Unsupervised Pre-training Help Deep Learning?
D. Erhan, A. Courville, Y. Bengio and P. Vincent [abs] [pdf]

Parallelizable Sampling of Markov Random Fields
J. Martens and I. Sutskever [abs] [pdf]

Posters from Breaking-News Abstracts

Nested sampling and the foundations of computational inference
J. Skilling

Analysis of finite sample effects in compressed Fisher's LDA
R.J. Durrant and A. Kaban

Optimal rates for conjugate gradient regularization
G. Blanchard and N. Kramer

How to save feature extraction time for fast and robust classification?
J. Louradour and C. Kermorvant

Greedy learning of binary latent trees
S. Narmeling and C.K.I. Williams

Bayesian spatial models for hospital recruitment using integrated nested Laplace approximation
M. Musio, E.-A. Sauleau and V. Mameli

Estimating the contribution of non-genetic factors to gene expression using GP-LVM
N. Fusi and N. Lawrence

Drifting linear dynamics
T. Raiko, A. Ilin, N. Korsakova, E. Oja and L. Valpola

Likelihood unimodality of a state-space model with point process observations
K. Yuan and M. Niranjan

Learning the iHMM through iterative map-reduce
S. Bratieres, J. van Gael, A. Vlachos and Z. Ghahramani

Classification of functional data: a weighted distance approach
A.M. Alonso, D. Casado and J.J. Romo