{"total":17,"rows":[{"id":"2102.03324","title":"GIBBON: General-purpose Information-Based Bayesian OptimisatioN","created":"2021-02-05","cited_by_count":47,"area":null},{"id":"2211.06149","title":"Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization","created":"2022-11-11","cited_by_count":16,"area":null},{"id":"2202.00060","title":"SnAKe: Bayesian Optimization with Pathwise Exploration","created":"2022-01-31","cited_by_count":14,"area":null},{"id":"2201.06834","title":"Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale","created":"2022-01-18","cited_by_count":13,"area":null},{"id":"2505.21034","title":"LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms","created":"2025-05-27","cited_by_count":10,"area":null},{"id":"2110.09334","title":"A portfolio approach to massively parallel Bayesian optimization","created":"2021-10-18","cited_by_count":9,"area":null},{"id":"2106.15883","title":"Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL","created":"2021-06-30","cited_by_count":8,"area":null},{"id":"2109.05765","title":"DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture","created":"2021-09-13","cited_by_count":6,"area":null},{"id":"2207.00479","title":"Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization","created":"2022-07-01","cited_by_count":6,"area":null},{"id":"2206.13326","title":"A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design","created":"2022-06-27","cited_by_count":5,"area":null},{"id":"2209.04722","title":"Batch Bayesian Optimization via Particle Gradient Flows","created":"2022-09-10","cited_by_count":2,"area":null},{"id":"2402.04885","title":"A Unified Gaussian Process for Branching and Nested Hyperparameter Optimization","created":"2024-01-19","cited_by_count":0,"area":null},{"id":"2411.16206","title":"Scalable Batch Bayesian Optimization Via Subspace Acquisition Functions","created":"2024-11-25","cited_by_count":0,"area":null},{"id":"2603.13501","title":"Standard Acquisition Is Sufficient for Asynchronous Bayesian Optimization","created":"2026-03-13","cited_by_count":0,"area":null},{"id":"2603.21180","title":"ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization","created":"2026-03-22","cited_by_count":0,"area":null},{"id":"2603.29730","title":"mlr3mbo: Bayesian Optimization in R","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2605.18819","title":"Efficient Conditioning Why Pseudo Observation Batch Bayesian Optimization Works When It Does not","created":"2026-05-12","cited_by_count":0,"area":null}],"next_cursor":null}