conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Bayesian Inference

5,566 papers

Papers per year

11
100
176
522
279
'05
'10
'15
'20
'25

Papers

Multi-Task Learning using Generalized t Process AISTATS 2010
Bayesian Generalized Kernel Models AISTATS 2010
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation JMLR 2010
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing JMLR 2010
Sparse Spectrum Gaussian Process Regression JMLR 2010
Practical Approaches to Principal Component Analysis in the Presence of Missing Values JMLR 2010
Mean Field Variational Approximation for Continuous-Time Bayesian Networks JMLR 2010
Expectation Truncation and the Benefits of Preselection In Training Generative Models JMLR 2010
Gaussian Processes for Machine Learning (GPML) Toolbox JMLR 2010
Inducing Tree-Substitution Grammars JMLR 2010
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes JMLR 2010
Classification with Incomplete Data Using Dirichlet Process Priors JMLR 2010
Learning Instance-Specific Predictive Models JMLR 2010
Incremental Sigmoid Belief Networks for Grammar Learning JMLR 2010
Preliminary Results in Decentralized Estimation for Single-Beacon Acoustic Underwater Navigation RSS 2010
Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data RSS 2010
Learning models of object structure NIPS 2009
Spatial Normalized Gamma Processes NIPS 2009
Free energy score space NIPS 2009
Multi-Label Prediction via Sparse Infinite CCA NIPS 2009
Non-stationary continuous dynamic Bayesian networks NIPS 2009
Gaussian process regression with Student-t likelihood NIPS 2009
Sensitivity analysis in HMMs with application to likelihood maximization NIPS 2009
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution NIPS 2009
A Stochastic approximation method for inference in probabilistic graphical models NIPS 2009