black-box optimization

Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach AISTATS 2019 Offline Contextual Bayesian Optimization NeurIPS 2019 Provably Robust Blackbox Optimization for Reinforcement Learning CoRL 2019 Scalable Global Optimization via Local Bayesian Optimization NeurIPS 2019 Trust Region Evolution Strategies AAAI 2019 ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization NeurIPS 2019 Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation NeurIPS 2018 Backpropagation through the Void: Optimizing control variates for black-box gradient estimation ICLR 2018 Multi-Fidelity Black-Box Optimization with Hierarchical Partitions ICML 2018 Policy Optimization by Genetic Distillation ICLR 2018 Structured Evolution with Compact Architectures for Scalable Policy Optimization ICML 2018 Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization NeurIPS 2018 A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space ACML 2017 Discovering and Exploiting Additive Structure for Bayesian Optimization AISTATS 2017 Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles JMLR 2017 Learning to Learn without Gradient Descent by Gradient Descent ICML 2017 Max-value Entropy Search for Efficient Bayesian Optimization ICML 2017 On Blackbox Backpropagation and Jacobian Sensing NeurIPS 2017 Task-based End-to-end Model Learning in Stochastic Optimization NeurIPS 2017 A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016 Black-box Optimization with a Politician ICML 2016 Black-Box Policy Search with Probabilistic Programs AISTATS 2016 Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NeurIPS 2016 Learning Using Anti-Training with Sacrificial Data JMLR 2016 Optimal Black-Box Reductions Between Optimization Objectives NeurIPS 2016