bayesian optimization

Query-Efficient Black-Box Red Teaming via Bayesian Optimization ACL 2023 Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds ICML 2023 Robust Bayesian Satisficing NeurIPS 2023 Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent NeurIPS 2023 Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes AISTATS 2023 Scaling Laws for Hyperparameter Optimization NeurIPS 2023 Self-Adjusting Weighted Expected Improvement for Bayesian Optimization AutoML 2023 Self-Correcting Bayesian Optimization through Bayesian Active Learning NeurIPS 2023 Sparse Bayesian optimization AISTATS 2023 Symbolic Explanations for Hyperparameter Optimization AutoML 2023 The Behavior and Convergence of Local Bayesian Optimization NeurIPS 2023 Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes ICML 2023 Transfer NAS with Meta-learned Bayesian Surrogates ICLR 2023 Two-stage Kernel Bayesian Optimization in High Dimensions UAI 2023 Unexpected Improvements to Expected Improvement for Bayesian Optimization NeurIPS 2023 Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction CVPR 2023 Variational Gaussian Processes with Decoupled Conditionals NeurIPS 2023 “Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization NeurIPS 2023 πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization ICLR 2022 A Bayesian Approach for Stochastic Continuum-armed Bandit with Long-term Constraints AISTATS 2022 Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders ICML 2022 Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization AISTATS 2022 Adaptive Gating for Single-Photon 3D Imaging CVPR 2022 Adversarial Attacks on Gaussian Process Bandits ICML 2022 A General Recipe for Likelihood-free Bayesian Optimization ICML 2022