Bayesian Learning

Probabilistic preference learning with the Mallows rank model JMLR 2018 Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures AISTATS 2018 Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors ICML 2018 Random Feature Stein Discrepancies NeurIPS 2018 Rectangular Bounding Process NeurIPS 2018 Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior NeurIPS 2018 Robust Learning of Fixed-Structure Bayesian Networks NeurIPS 2018 Scalable approximate Bayesian inference for particle tracking data ICML 2018 Scalable Bayes via Barycenter in Wasserstein Space JMLR 2018 Scalable Hyperparameter Transfer Learning NeurIPS 2018 Scaling Gaussian Process Regression with Derivatives NeurIPS 2018 Sensitivity to Input Order: Evaluation of an Incremental and Memory-Limited Bayesian Cross-Situational Word Learning Model COLING 2018 SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient NeurIPS 2018 Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation CoRL 2018 Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection ICML 2018 Stagewise Safe Bayesian Optimization with Gaussian Processes ICML 2018 Stochastic Nonparametric Event-Tensor Decomposition NeurIPS 2018 Stochastic Variance-Reduced Hamilton Monte Carlo Methods ICML 2018 Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors ICML 2018 Temporal alignment and latent Gaussian process factor inference in population spike trains NeurIPS 2018 The Binary Space Partitioning-Tree Process AISTATS 2018 The Finite Model Theory of Bayesian Networks: Descriptive Complexity IJCAI 2018 The promises and pitfalls of Stochastic Gradient Langevin Dynamics NeurIPS 2018 Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning NeurIPS 2018 Variational inference for the multi-armed contextual bandit AISTATS 2018