acquisition function

Bayesian Active Learning with Fully Bayesian Gaussian Processes NeurIPS 2022 Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization NeurIPS 2022 Class-Balanced Active Learning for Image Classification WACV 2022 Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization RSS 2022 Deep Multi-Fidelity Active Learning of High-Dimensional Outputs AISTATS 2022 Generalizing Bayesian Optimization with Decision-theoretic Entropies NeurIPS 2022 Human-AI Collaborative Bayesian Optimisation NeurIPS 2022 Joint Entropy Search For Maximally-Informed Bayesian Optimization NeurIPS 2022 Joint Entropy Search for Multi-Objective Bayesian Optimization NeurIPS 2022 Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation AISTATS 2022 Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels NeurIPS 2022 Pareto Set Learning for Expensive Multi-Objective Optimization NeurIPS 2022 Spectral Representation of Robustness Measures for Optimization Under Input Uncertainty ICML 2022 Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces NeurIPS 2022 Triangulation candidates for Bayesian optimization NeurIPS 2022 Active Learning by Acquiring Contrastive Examples EMNLP 2021 Active Learning for Argument Strength Estimation EMNLP 2021 Active Learning for Bayesian 3D Hand Pose Estimation WACV 2021 Active Testing: Sample-Efficient Model Evaluation ICML 2021 An Empirical Study of Bayesian Optimization: Acquisition Versus Partition JMLR 2021 An Information-Theoretic Framework for Unifying Active Learning Problems AAAI 2021 Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? JMLR 2021 BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search AAAI 2021 Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty AISTATS 2021 Bayesian Optimization of Function Networks NeurIPS 2021