Bayesian Optimization

An Empirical Bayes Approach to Optimizing Machine Learning Algorithms NeurIPS 2017 Deep Kernels for Optimizing Locomotion Controllers CoRL 2017 Efficient Automatic Perception System Parameter Tuning On Site without Expert Supervision CoRL 2017 High Dimensional Bayesian Optimization using Dropout IJCAI 2017 Improving the Expected Improvement Algorithm NeurIPS 2017 Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NeurIPS 2017 Learning to select data for transfer learning with Bayesian Optimization EMNLP 2017 Lookahead Bayesian Optimization with Inequality Constraints NeurIPS 2017 Multi-Information Source Optimization NeurIPS 2017 A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016 Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition NeurIPS 2016 Bayesian optimization for automated model selection NeurIPS 2016 Bayesian Optimization for Probabilistic Programs NeurIPS 2016 Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian NeurIPS 2016 Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach NeurIPS 2016 Double Thompson Sampling for Dueling Bandits NeurIPS 2016 Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NeurIPS 2016 Learning under uncertainty: a comparison between R-W and Bayesian approach NeurIPS 2016 Optimistic Gittins Indices NeurIPS 2016 Poisson-Gamma dynamical systems NeurIPS 2016 Predictive Entropy Search for Multi-objective Bayesian Optimization ICML 2016 The Parallel Knowledge Gradient Method for Batch Bayesian Optimization NeurIPS 2016 Threshold Learning for Optimal Decision Making NeurIPS 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NeurIPS 2016 Bayesian Optimization with Exponential Convergence NeurIPS 2015