Bayesian & Probabilistic

Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling NeurIPS 2012 Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models NeurIPS 2012 From Deformations to Parts: Motion-based Segmentation of 3D Objects NeurIPS 2012 Gaussian Processes for time-marked time-series data AISTATS 2012 Graphical Gaussian Vector for Image Categorization NeurIPS 2012 Graphical Models via Generalized Linear Models NeurIPS 2012 Hierarchical spike coding of sound NeurIPS 2012 Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints NeurIPS 2012 How Prior Probability Influences Decision Making: A Unifying Probabilistic Model NeurIPS 2012 How They Vote: Issue-Adjusted Models of Legislative Behavior NeurIPS 2012 Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression AISTATS 2012 Informative Priors for Markov Blanket Discovery AISTATS 2012 Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation NeurIPS 2012 Joint Modeling of a Matrix with Associated Text via Latent Binary Features NeurIPS 2012 Kernel Topic Models AISTATS 2012 Label Ranking with Partial Abstention based on Thresholded Probabilistic Models NeurIPS 2012 Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NeurIPS 2012 Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs NeurIPS 2012 Learning as MAP Inference in Discrete Graphical Models NeurIPS 2012 Learning curves for multi-task Gaussian process regression NeurIPS 2012 Learning from Distributions via Support Measure Machines NeurIPS 2012 Learning From Ordered Sets and Applications in Collaborative Ranking ACML 2012 Learning from the Wisdom of Crowds by Minimax Entropy NeurIPS 2012 Learning Invariant Representations of Molecules for Atomization Energy Prediction NeurIPS 2012 Learning Label Trees for Probabilistic Modelling of Implicit Feedback NeurIPS 2012