Bayesian & Probabilistic

Probabilistic Multi-Task Feature Selection NeurIPS 2010 Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models NeurIPS 2010 (RF)^2 -- Random Forest Random Field NeurIPS 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010 Shadow Dirichlet for Restricted Probability Modeling NeurIPS 2010 Simple Exponential Family PCA AISTATS 2010 Slice sampling covariance hyperparameters of latent Gaussian models NeurIPS 2010 Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms AISTATS 2010 Sparse Instrumental Variables (SPIV) for Genome-Wide Studies NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 State-Space Inference and Learning with Gaussian Processes AISTATS 2010 Structured Determinantal Point Processes NeurIPS 2010 Supervised Dimension Reduction Using Bayesian Mixture Modeling AISTATS 2010 Switched Latent Force Models for Movement Segmentation NeurIPS 2010 Switching state space model for simultaneously estimating state transitions and nonstationary firing rates NeurIPS 2010 Synergies in learning words and their referents NeurIPS 2010 The Maximal Causes of Natural Scenes are Edge Filters NeurIPS 2010 The Multidimensional Wisdom of Crowds NeurIPS 2010 The Neural Costs of Optimal Control NeurIPS 2010 Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Unsupervised Aggregation for Classification Problems with Large Numbers of Categories AISTATS 2010 Variational bounds for mixed-data factor analysis NeurIPS 2010 Variational Inference over Combinatorial Spaces NeurIPS 2010 Variational methods for Reinforcement Learning AISTATS 2010