Bayesian & Probabilistic

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution NeurIPS 2015 Convergence rate of Bayesian tensor estimator and its minimax optimality ICML 2015 Convolutional spike-triggered covariance analysis for neural subunit models NeurIPS 2015 Copula variational inference NeurIPS 2015 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions NeurIPS 2015 Curriculum Learning of Bayesian Network Structures ACML 2015 Decision Boundary for Discrete Bayesian Network Classifiers JMLR 2015 Deeply Learning the Messages in Message Passing Inference NeurIPS 2015 Deep Poisson Factor Modeling NeurIPS 2015 Deep Temporal Sigmoid Belief Networks for Sequence Modeling NeurIPS 2015 Differentially Private Bayesian Optimization ICML 2015 Differentially Private Learning of Structured Discrete Distributions NeurIPS 2015 Efficient and Robust Automated Machine Learning NeurIPS 2015 Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression NeurIPS 2015 Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015 Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces NeurIPS 2015 Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015 Estimating Mixture Models via Mixtures of Polynomials NeurIPS 2015 Exactness of Approximate MAP Inference in Continuous MRFs NeurIPS 2015 Expectation Particle Belief Propagation NeurIPS 2015 Expectation Propagation for Rectified Linear Poisson Regression ACML 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015 Face Alignment Using Cascade Gaussian Process Regression Trees CVPR 2015 Fast and Accurate Inference of Plackett–Luce Models NeurIPS 2015