{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T05:06:13Z","timestamp":1775365573655,"version":"3.50.1"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tsp.2025.3559568","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T18:07:34Z","timestamp":1744394854000},"page":"2039-2052","source":"Crossref","is-referenced-by-count":4,"title":["Robust Bayesian Optimization via Localized Online Conformal Prediction"],"prefix":"10.1109","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8870-4664","authenticated-orcid":false,"given":"Dongwon","family":"Kim","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3458-2881","authenticated-orcid":false,"given":"Matteo","family":"Zecchin","sequence":"additional","affiliation":[{"name":"King’s Communications, Learning & Information Processing (KCLIP) Lab, Centre for Intelligent Information Processing Systems (CIIPS), Department of Engineering, King’s College London, London, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4091-7860","authenticated-orcid":false,"given":"Sangwoo","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Imperial College London, London, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5508-3742","authenticated-orcid":false,"given":"Joonhyuk","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9898-3209","authenticated-orcid":false,"given":"Osvaldo","family":"Simeone","sequence":"additional","affiliation":[{"name":"King’s Communications, Learning & Information Processing (KCLIP) Lab, Centre for Intelligent Information Processing Systems (CIIPS), Department of Engineering, King’s College London, London, U.K."}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3144939"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2023.3287240"},{"key":"ref3","first-page":"1674","article-title":"Input warping for Bayesian optimization of non-stationary functions","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Snoek","year":"2014"},{"key":"ref4","first-page":"970","article-title":"Modulating surrogates for Bayesian optimization","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bodin","year":"2020"},{"key":"ref5","first-page":"3004","article-title":"Misspecified Gaussian Process bandit optimization","author":"Bogunovic","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/ac298c"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.3028830"},{"key":"ref8","article-title":"Quantifying mismatch in Bayesian optimization","author":"Schulz","year":"2016","journal-title":"Nips Workshop on Bayesian Optimization: Black-Box Optimization and beyond"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2494218"},{"key":"ref10","first-page":"936","article-title":"Uncertainty quantification using martingales for misspecified Gaussian processes","volume-title":"Algorithmic Learning Theory","author":"Neiswanger","year":"2021"},{"key":"ref11","first-page":"959","article-title":"Bayesian optimization with conformal prediction sets","volume-title":"Proc. Int Nat. Conf. Artif. Intell. Statist.","author":"Stanton","year":"2023"},{"key":"ref12","first-page":"1450","article-title":"Online calibrated and conformal prediction improves Bayesian optimization","volume-title":"Proc. Int Nat. Conf. Artif. Intell. Statist.","author":"Deshpande","year":"2024"},{"key":"ref13","first-page":"8165","article-title":"Localized adaptive risk control","volume-title":"Advances in Neural Information Processing Systems","author":"Zecchin","year":"2024"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2022.3200376"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1137\/17M1129179"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SPAWC51304.2022.9833993"},{"key":"ref17","article-title":"Meta-learning acquisition functions for transfer learning in Bayesian optimization","author":"Volpp","year":"2019"},{"key":"ref18","first-page":"237","article-title":"Meta-learning priors for safe Bayesian optimization","volume-title":"Proc. Conf. Robot Learn.","author":"Rothfuss","year":"2023"},{"key":"ref19","first-page":"1305","article-title":"Active learning for misspecified models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sugiyama","year":"2005"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3982\/TE2480"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107103"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3038333"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/b106715"},{"key":"ref24","article-title":"A gentle introduction to conformal prediction and distribution-free uncertainty quantification","author":"Angelopoulos","year":"2021"},{"key":"ref25","first-page":"1660","article-title":"Adaptive conformal inference under distribution shift","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Gibbs","year":"2021"},{"key":"ref26","article-title":"Online conformal prediction with decaying step sizes","author":"Angelopoulos","year":"2024"},{"key":"ref27","article-title":"Achieving risk control in online learning settings","author":"Feldman"},{"key":"ref28","first-page":"2526","article-title":"Conformal prediction under covariate shift","volume-title":"Proc. Adv. Neural Inform. Process. Syst.","author":"Tibshirani","year":"2019"},{"key":"ref29","article-title":"Conformal prediction with localization","author":"Guan","year":"2019"},{"key":"ref30","first-page":"2022","article-title":"Conformal inference for online prediction with arbitrary distribution shifts","author":"Gibbs"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1093\/jrsssb\/qkae103"},{"key":"ref32","first-page":"822","article-title":"Hierarchically-partitioned gaussian process approximation","volume-title":"Artificial Intelligence and Statistics","author":"Lee","year":"2017"},{"key":"ref33","first-page":"5497","article-title":"Scalable global optimization via local Bayesian optimization","volume-title":"Proc. Adv. Neural Inform. Process. Syst.","author":"Eriksson","year":"2019"},{"key":"ref34","volume-title":"Virtual Library of Simulation Experiments: Test Functions and Datasets","volume":"13","author":"Surjanovic","year":"2013"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM54140.2023.10437768"},{"key":"ref36","volume-title":"Gaussian Processes for Machine Learning","volume":"2","author":"Williams","year":"2006"},{"key":"ref37","article-title":"Gaussian process optimization in the bandit setting: No regret and experimental design","author":"Srinivas","year":"2009"},{"key":"ref38","article-title":"The reparameterization trick for acquisition functions","author":"Wilson","year":"2017"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2004.830991"},{"key":"ref40","article-title":"From conformal predictions to confidence regions","author":"Guille-Escuret","year":"2024"},{"key":"ref41","first-page":"2951","article-title":"Practical Bayesian optimization of machine learning algorithms","volume-title":"Proc. Adv. Neural Inform. Process. Syst.","author":"Snoek","year":"2012"},{"key":"ref42","article-title":"A tutorial on Bayesian optimization","author":"Frazier","year":"2018"},{"key":"ref43","first-page":"681","article-title":"Bayesian learning via stochastic gradient Langevin dynamics","volume-title":"Proc. Int. Conf. on Mach. Learn.","author":"Welling","year":"2011"},{"key":"ref44","first-page":"3627","article-title":"Max-value entropy search for efficient Bayesian optimization","volume-title":"Proc. Int. Conf. on Mach. Learn.","author":"Wang","year":"2017"},{"key":"ref45","article-title":"Study on Channel Model for Frequencies from 0.5 to 100 GHz (Release 16)","year":"2019"},{"key":"ref46","first-page":"23047","article-title":"Conformal PID control for time series prediction","volume-title":"Proc. Adv. Neural Inform. Process. Syst.","author":"Angelopoulos","year":"2023"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/tsp.2025.3528252"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/78\/10807692\/10964108.pdf?arnumber=10964108","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T17:41:43Z","timestamp":1750268503000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10964108\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/tsp.2025.3559568","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"value":"1053-587X","type":"print"},{"value":"1941-0476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}