Probabilistic Modeling

Monte Carlo Methods for Maximum Margin Supervised Topic Models NeurIPS 2012 Multiplicative Forests for Continuous-Time Processes NeurIPS 2012 Multiresolution Gaussian Processes NeurIPS 2012 Multiresolution Mixture Modeling using Merging of Mixture Components ACML 2012 Natural Images, Gaussian Mixtures and Dead Leaves NeurIPS 2012 Near-Optimal MAP Inference for Determinantal Point Processes NeurIPS 2012 Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012 Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NeurIPS 2012 Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions NeurIPS 2012 Nonparanormal Belief Propagation (NPNBP) NeurIPS 2012 On Estimation and Selection for Topic Models AISTATS 2012 On Lifting the Gibbs Sampling Algorithm NeurIPS 2012 Online Sum-Product Computation Over Trees NeurIPS 2012 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks NeurIPS 2012 PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012 Perfect Dimensionality Recovery by Variational Bayesian PCA NeurIPS 2012 Persistent Homology for Learning Densities with Bounded Support NeurIPS 2012 Priors for Diversity in Generative Latent Variable Models NeurIPS 2012 Probabilistic acoustic tube: a probabilistic generative model of speech for speech analysis/synthesis AISTATS 2012 Probabilistic Event Cascades for Alzheimer's disease NeurIPS 2012 Probabilistic Low-Rank Subspace Clustering NeurIPS 2012 Probabilistic n-Choose-k Models for Classification and Ranking NeurIPS 2012 Proper losses for learning from partial labels NeurIPS 2012