Bayesian Optimization

Black-box optimization of noisy functions with unknown smoothness NeurIPS 2015 Differentially Private Bayesian Optimization ICML 2015 Efficient and Robust Automated Machine Learning NeurIPS 2015 Improving Object Detection With Deep Convolutional Networks via Bayesian Optimization and Structured Prediction CVPR 2015 Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions NeurIPS 2015 Predictive Entropy Search for Bayesian Optimization with Unknown Constraints ICML 2015 Probabilistic Line Searches for Stochastic Optimization NeurIPS 2015 The Human Kernel NeurIPS 2015 On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning AISTATS 2014 Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors AISTATS 2014 Predictive Entropy Search for Efficient Global Optimization of Black-box Functions NeurIPS 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search NeurIPS 2013 Bayesian optimization explains human active search NeurIPS 2013 High-Dimensional Gaussian Process Bandits NeurIPS 2013 Multi-Task Bayesian Optimization NeurIPS 2013 Optimizing Instructional Policies NeurIPS 2013 Prior-free and prior-dependent regret bounds for Thompson Sampling NeurIPS 2013 Thompson Sampling for 1-Dimensional Exponential Family Bandits NeurIPS 2013 Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search NeurIPS 2012 Multiplicative Forests for Continuous-Time Processes NeurIPS 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Algorithms for Hyper-Parameter Optimization NeurIPS 2011 Contextual Gaussian Process Bandit Optimization NeurIPS 2011 Information Rates and Optimal Decoding in Large Neural Populations NeurIPS 2011