[Artificial Intelligence and Statistics Logo] Artificial Intelligence and Statistics 2010


AISTATS Conference Schedule

Poster Session II, Friday May 14

Contributed Posters

Posters from Breaking-News Abstracts

Contributed Posters

On the Impact of Kernel Approximation on Learning Accuracy
C. Cortes, M. Mohri and A. Talwalkar [abs] [pdf]

Kernel Partial Least Squares is Universally Consistent
G. Blanchard and N. Krämer [abs] [pdf]

Risk Bounds for Levy Processes in the PAC-Learning Framework
C. Zhang and D. Tao [abs] [pdf]

Negative Results for Active Learning with Convex Losses
S. Hanneke and L. Yang [abs] [pdf]

Impossibility Theorems for Domain Adaptation
S. Ben David, T. Lu, T. Luu and D. Pal [abs] [pdf]

Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
X. Zhang, T. Graepel and R. Herbrich [abs] [pdf]

Infinite Predictor Subspace Models for Multitask Learning
P. Rai and H. Daume III [abs] [pdf]

Neural conditional random fields
T. Do and T. Artieres [abs] [pdf]

Structured Prediction Cascades
D. Weiss and B. Taskar [abs] [pdf]

Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
S. Kakade, O. Shamir, K. Sindharan and A. Tewari [abs] [pdf] [supplementary]

Feature Selection using Multiple Streams
P. Dhillon, D. Foster and L. Ungar [abs] [pdf]

Fast Active-set-type Algorithms for L1-regularized Linear Regression
J. Kim and H. Park [abs] [pdf]

Nonparametric prior for adaptive sparsity
V. Raykar and L. Zhao [abs] [pdf]

Elliptical slice sampling
I. Murray, R. Adams and D. MacKay [abs] [pdf] [supplementary]

Multi-Task Learning using Generalized t Process
Y. Zhang and D. Yeung [abs] [pdf] [supplementary]

Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
M. Alvarez, D. Luengo, M. Titsias and N. Lawrence [abs] [pdf]

Gaussian processes with monotonicity information
J. Riihimäki and A. Vehtari [abs] [pdf]

On the Convergence Properties of Contrastive Divergence
I. Sutskever and T. Tieleman [abs] [pdf]

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
G. Desjardins, A. Courville, Y. Bengio, P. Vincent and O. Delalleau [abs] [pdf]

Learning with Blocks: Composite Likelihood and Contrastive Divergence
A. Asuncion, Q. Liu, A. Ihler and P. Smyth [abs] [pdf]

Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching
N. Schraudolph [abs] [pdf]

HOP-MAP: Efficient Message Passing with High Order Potentials
D. Tarlow, I. Givoni and R. Zemel [abs] [pdf]

Why are DBNs sparse?
S. Chatterjee and S. Russell [abs] [pdf]

Graphical Gaussian modelling of multivariate time series with latent variables
M. Eichler [abs] [pdf]

Approximation of hidden Markov models by mixtures of experts with application to particle filtering
J. Olsson and J. Ströjby [abs] [pdf]

Learning Nonlinear Dynamic Models from Non-sequenced Data
T. Huang, L. Song and J. Schneider [abs] [pdf]

Nonparametric Bayesian Matrix Factorization by Power-EP
N. Ding, Y. Qi, R. Xiang, I. Molloy and N. Li [abs] [pdf]

Collaborative Filtering on a Budget
A. Karatzoglou, A. Smola and M. Weimer [abs] [pdf]

Collaborative Filtering via Rating Concentration
B. Huang and T. Jebara [abs] [pdf]

Descent Methods for Tuning Parameter Refinement
A. Lorbert and P. Ramadge [abs] [pdf]

Learning Policy Improvements with Path Integrals
E. Theodorou, J. Buchli and S. Schaal [abs] [pdf]

Efficient Reductions for Imitation Learning
S. Ross and D. Bagnell [abs] [pdf] [supplementary]

A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping
P. Torma, A. György and C. Szepesvári [abs] [pdf]

Incremental Sparsification for Real-time Online Model Learning
D. Nguyen–Tuong and J. Peters [abs] [pdf]

Posters from Breaking-News Abstracts

On predictive distributions in fuzzy Bayesian inference
R. Viertl

Proximal methods for sparse hierarchical dictionary learning
R. Jenatton, J. Mairal, G. Obozinski and F. Bach

Estimation in the Burr X parameters and reliability using lower records
A. Bazlizi

Web scale image annotation: learning to rank with joint word-image embeddings
J. Weston, S. Bengio and N. Usunier

Unlearning for better mixing
O. Breuleux, Y. Bengio and P. Vincent

TREERANK: a statistical software for bipartite ranking
N. Basklotis, S. Clemencon, M. Depecker and N. Vayatis

Online semi-supervised learning on quantized graphs
M. Valko, B. Kveton and L. Huang

Enhancing the efficieny of spectral clustering with partial supervision
D. Mavroeidis

Non-parametric change detection using sequential kernel density estimation
G.J. Ross, D.K. Tasoulis and N.M. Adams

Finding the MAP configuration of a subset of latent variables in a graphical model with discrete variables
G. Teodoru, C. Blundell and M. Sahani

A statistical test to detect distance concentration from data sets
A. Kaban

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