Bayesian & Probabilistic

Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NeurIPS 2012 Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions NeurIPS 2012 Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction 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 Learning of a Dirichlet Process Mixture of Generalized Dirichlet Distributions for Simultaneous Clustering and Localized Feature Selection ACML 2012 Online Sum-Product Computation Over Trees NeurIPS 2012 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012 On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference RSS 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 Phoneme Classification using Constrained Variational Gaussian Process Dynamical System NeurIPS 2012 Practical Bayesian Optimization of Machine Learning Algorithms 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 Random function priors for exchangeable arrays with applications to graphs and relational data NeurIPS 2012 Randomized Optimum Models for Structured Prediction AISTATS 2012