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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Efficient Learning of Deep Boltzmann Machines AISTATS 2010
Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010
A Study of Approximate Inference in Probabilistic Relational Models ACML 2010
Generative Models of Information Diffusion with Asynchronous Timedelay ACML 2010
An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models ACML 2010
Dense Message Passing for Sparse Principal Component Analysis AISTATS 2010
On the Convergence Properties of Contrastive Divergence AISTATS 2010
Inference and Learning in Networks of Queues AISTATS 2010
HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010
Unsupervised Aggregation for Classification Problems with Large Numbers of Categories AISTATS 2010
State-Space Inference and Learning with Gaussian Processes AISTATS 2010
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010
An Alternative Prior Process for Nonparametric Bayesian Clustering AISTATS 2010
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NIPS 2010
Factor Modeling for Advertisement Targeting NIPS 2009
A Stochastic approximation method for inference in probabilistic graphical models NIPS 2009
Sensitivity analysis in HMMs with application to likelihood maximization NIPS 2009
Rethinking LDA: Why Priors Matter NIPS 2009
Spatial Normalized Gamma Processes NIPS 2009
Local Rules for Global MAP: When Do They Work ? NIPS 2009
A Bayesian Analysis of Dynamics in Free Recall NIPS 2009
Structural inference affects depth perception in the context of potential occlusion NIPS 2009
Indian Buffet Processes with Power-law Behavior NIPS 2009
Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NIPS 2009
Posterior vs Parameter Sparsity in Latent Variable Models NIPS 2009