density estimation

Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields AISTATS 2012 Semi-Supervised Domain Adaptation with Non-Parametric Copulas NeurIPS 2012 The Time-Marginalized Coalescent Prior for Hierarchical Clustering NeurIPS 2012 Bagged Structure Learning of Bayesian Network AISTATS 2011 Bounds on Individual Risk for Log-loss Predictors COLT 2011 Dirichlet Process Mixtures of Generalized Linear Models JMLR 2011 Discussion of “The Neural Autoregressive Distribution Estimator” AISTATS 2011 Forest Density Estimation JMLR 2011 Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization ACML 2011 Scalable Training of Mixture Models via Coresets NeurIPS 2011 The Neural Autoregressive Distribution Estimator AISTATS 2011 Learning To Count Objects in Images NeurIPS 2010 Noise-contrastive estimation: A new estimation principle for unnormalized statistical models AISTATS 2010 Rates of convergence for the cluster tree NeurIPS 2010 Regularized estimation of image statistics by Score Matching NeurIPS 2010 Semi-Supervised Novelty Detection JMLR 2010 Spectral Regularization for Support Estimation NeurIPS 2010 Submanifold density estimation NeurIPS 2009 Near-minimax recursive density estimation on the binary hypercube NeurIPS 2008 Performance analysis for L\_2 kernel classification NeurIPS 2008 The Gaussian Process Density Sampler NeurIPS 2008 Classification via Minimum Incremental Coding Length (MICL) NeurIPS 2007 Density Estimation under Independent Similarly Distributed Sampling Assumptions NeurIPS 2007 Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation NeurIPS 2007 Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption JMLR 2007