{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:24:46Z","timestamp":1775143486655,"version":"3.50.1"},"reference-count":55,"publisher":"Informa UK Limited","issue":"3","content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational and Graphical Statistics"],"published-print":{"date-parts":[[2024,7,2]]},"DOI":"10.1080\/10618600.2024.2308216","type":"journal-article","created":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T17:14:49Z","timestamp":1706030089000},"page":"855-868","update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":7,"title":["Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization"],"prefix":"10.1080","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9254-8342","authenticated-orcid":false,"given":"Hengrui","family":"Luo","sequence":"first","affiliation":[{"name":"Lawrence Berkeley National Laboratory, Berkeley, CA"}]},{"given":"Younghyun","family":"Cho","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA"}]},{"given":"James W.","family":"Demmel","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA"}]},{"given":"Xiaoye S.","family":"Li","sequence":"additional","affiliation":[{"name":"Lawrence Berkeley National Laboratory, Berkeley, CA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3750-1178","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Lawrence Berkeley National Laboratory, Berkeley, CA"}]}],"member":"301","published-online":{"date-parts":[[2024,3,8]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.3389\/fbuil.2017.00052"},{"key":"e_1_3_4_3_1","first-page":"397","article-title":"\u201cUsing Confidence Bounds for Exploitation-Exploration Trade-Offs,\u201d","volume":"3","author":"Auer P.","year":"2002","unstructured":"Auer, P. (2002), \u201cUsing Confidence Bounds for Exploitation-Exploration Trade-Offs,\u201d Journal of Machine Learning Research, 3, 397\u2013422.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_4_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2018.2841200"},{"key":"e_1_3_4_5_1","article-title":"\u201cAlgorithms for Hyper-Parameter Optimization,\u201d","volume":"24","author":"Bergstra J.","year":"2011","unstructured":"Bergstra, J., Bardenet, R., Bengio, Y., and K\u00e9gl, B. (2011), \u201cAlgorithms for Hyper-Parameter Optimization,\u201d in Advances in Neural Information Processing Systems (Vol. 24).","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_4_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-73249-3_2"},{"key":"e_1_3_4_7_1","first-page":"39047","article-title":"\u201cStructural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport,\u201d","volume":"35","author":"Bitzer M.","year":"2022","unstructured":"Bitzer, M., Meister, M., and Zimmer, C. (2022), \u201cStructural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport,\u201d in Advances in Neural Information Processing Systems (Vol. 35), pp. 39047\u201339058.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_4_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10472-020-09712-4"},{"key":"e_1_3_4_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-018-5724-2"},{"key":"e_1_3_4_10_1","doi-asserted-by":"publisher","DOI":"10.1214\/09-AOAS285"},{"key":"e_1_3_4_11_1","article-title":"\u201cKernel Methods for Deep Learning,\u201d","volume":"22","author":"Cho Y.","year":"2009","unstructured":"Cho, Y., and Saul, L. (2009), \u201cKernel Methods for Deep Learning,\u201d in Advances in Neural Information Processing Systems (Vol. 22).","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_4_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2016.1211554"},{"key":"e_1_3_4_13_1","unstructured":"Deshwal A. Belakaria S. and Doppa J. R. (2021) \u201cBayesian Optimization over Hybrid Spaces \u201d arXiv preprint arXiv:2106.04682."},{"key":"e_1_3_4_14_1","first-page":"1997","article-title":"\u201cNeural Architecture Search: A Survey,\u201d","volume":"20","author":"Elsken T.","year":"2019","unstructured":"Elsken, T., Metzen, J. H., and Hutter, F. (2019), \u201cNeural Architecture Search: A Survey,\u201d The Journal of Machine Learning Research, 20, 1997\u20132017.","journal-title":"The Journal of Machine Learning Research"},{"key":"e_1_3_4_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330862"},{"key":"e_1_3_4_16_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176347963"},{"key":"e_1_3_4_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.11.004"},{"key":"e_1_3_4_18_1","unstructured":"Ghysels P. Ch\u00e1vez G. Guo L. Gorman C. Li X. S. Liu Y. Rebrova L. Rouet F.-H. Mary T. and Actor J. (2017) \u201cSTRUMPACK.\u201d"},{"key":"e_1_3_4_19_1","doi-asserted-by":"publisher","DOI":"10.1137\/15M1010117"},{"key":"e_1_3_4_20_1","first-page":"5470","volume-title":"Proceedings of the 32nd International Conference on Neural Information Processing Systems","author":"Gopakumar S.","year":"2018","unstructured":"Gopakumar, S., Gupta, S., Rana, S., Nguyen, V., and Venkatesh, S. (2018), \u201cAlgorithmic Assurance: An Active Approach to Algorithmic Testing Using Bayesian Optimisation,\u201d in Proceedings of the 32nd International Conference on Neural Information Processing Systems, pp. 5470\u20135478."},{"key":"e_1_3_4_21_1","doi-asserted-by":"publisher","DOI":"10.1201\/9780367815493"},{"key":"e_1_3_4_22_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1979.tb01072.x"},{"key":"e_1_3_4_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/0095-0696(78)90006-2"},{"key":"e_1_3_4_24_1","volume-title":"Scikit-Optimize\/Scikit-Optimize","author":"Head T.","year":"2020","unstructured":"Head, T., Kumar, M., Nahrstaedt, H., Louppe, G., and Shcherbatyi, I. (2020), \u201cScikit-Optimize\/Scikit-Optimize,\u201d Zenodo."},{"key":"e_1_3_4_25_1","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00200"},{"key":"e_1_3_4_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25566-3_40"},{"key":"e_1_3_4_27_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008306431147"},{"key":"e_1_3_4_28_1","first-page":"48","volume-title":"Benelux Conference on Artificial Intelligence","author":"Karlsson R.","year":"2020","unstructured":"Karlsson, R., Bliek, L., Verwer, S., and de Weerdt, M. (2020), \u201cContinuous Surrogate-based Optimization Algorithms are Well-suited for Expensive Discrete Problems,\u201d in Benelux Conference on Artificial Intelligence, pp. 48\u201363, Springer."},{"key":"e_1_3_4_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/11871842_29"},{"key":"e_1_3_4_30_1","unstructured":"Liao Y.-T. Luo H. and Ma A. (2023) \u201cEfficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization \u201d arXiv preprint arXiv:2306.00357."},{"key":"e_1_3_4_31_1","unstructured":"Luo H. Demmel J. W. Cho Y. Li X. S. and Liu Y. (2021) \u201cNon-smooth Bayesian Optimization in Tuning Problems \u201d arXiv preprint arXiv:2109.07563."},{"key":"e_1_3_4_32_1","doi-asserted-by":"crossref","unstructured":"Luo H. and Pratola M. T. (2022) \u201cSharded Bayesian Additive Regression Trees \u201d arXiv:2306.00361 pp. 1\u201346.","DOI":"10.1002\/9781118445112.stat08288"},{"key":"e_1_3_4_33_1","unstructured":"Luo H. and Zhu Y. (2023) \u201cOptimism and Model Complexity Measure for Linear Models \u201d in preparation."},{"key":"e_1_3_4_34_1","first-page":"6511","volume-title":"International Conference on Machine Learning","author":"Lykouris T.","year":"2020","unstructured":"Lykouris, T., Mirrokni, V., and Leme, R. P. (2020), \u201cBandits with Adversarial Scaling,\u201d in International Conference on Machine Learning, pp. 6511\u20136521, PMLR."},{"key":"e_1_3_4_35_1","volume-title":"Advances in Neural Information Processing Systems","author":"Malkomes G.","year":"2016","unstructured":"Malkomes, G., Schaff, C., and Garnett, R. (2016), \u201cBayesian Optimization for Automated Model Selection,\u201d in Advances in Neural Information Processing Systems (Vol. 29), eds. D. Lee, M. Sugiyama, U. Luxburg, I. Guyon, and R. Garnett, Curran Associates, Inc."},{"key":"e_1_3_4_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5971"},{"key":"e_1_3_4_37_1","unstructured":"Oh C. Gavves E. and Welling M. (2021) \u201cMixed Variable Bayesian Optimization with Frequency Modulated Kernels \u201d arXiv preprint arXiv:2102.12792."},{"key":"e_1_3_4_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5_8"},{"key":"e_1_3_4_39_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/457"},{"key":"e_1_3_4_40_1","volume-title":"Gaussian Processes for Machine Learning. Adaptive Computation and Machine Learning","author":"Rasmussen C. E.","year":"2006","unstructured":"Rasmussen, C. E., and Williams, C. K. I. (2006), Gaussian Processes for Machine Learning. Adaptive Computation and Machine Learning, Cambridge, MA: MIT Press."},{"key":"e_1_3_4_41_1","unstructured":"Ru B. Alvi A. S. Nguyen V. Osborne M. A. and Roberts S. J. (2020) \u201cBayesian Optimisation over Multiple Continuous and Categorical Inputs \u201d arXiv:1906.08878 [cs stat]."},{"key":"e_1_3_4_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-307502-4.50023-4"},{"key":"e_1_3_4_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2494218"},{"key":"e_1_3_4_44_1","unstructured":"Sid-Lakhdar W. M. Aznaveh M. M. Li X. S. and Demmel J. W. (2019) \u201cMultitask and Transfer Learning for Autotuning Exascale Applications \u201d arXiv:1908.05792 [cs stat]."},{"key":"e_1_3_4_45_1","unstructured":"Sid-Lakhdar W. M. Cho Y. Demmel J. W. Luo H. Li X. S. Liu Y. and Marques O. (2020) \u201cGPTune User Guide.\u201d"},{"key":"e_1_3_4_46_1","doi-asserted-by":"publisher","DOI":"10.1088\/0067-0049\/214\/2\/24"},{"key":"e_1_3_4_47_1","unstructured":"Snoek J. Larochelle H. and Adams R. P. (2012) \u201cPractical Bayesian Optimization of Machine Learning Algorithms \u201d arXiv:1206.2944 [cs stat]."},{"key":"e_1_3_4_48_1","unstructured":"Surjanovic S. and Bingham D. (2022) \u201cVirtual Library of Simulation Experiments: Test Functions and Datasets \u201d available at http:\/\/www.sfu.ca\/\u223cssurjano."},{"key":"e_1_3_4_49_1","unstructured":"Swersky K. Duvenaud D. Snoek J. Hutter F. and Osborne M. A. (2014) \u201cRaiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces \u201d arXiv preprint arXiv:1409.4011."},{"key":"e_1_3_4_50_1","unstructured":"Tesauro G. Rajan V. and Segal R. (2012) \u201cBayesian Inference in Monte-Carlo Tree Search \u201d arXiv preprint arXiv:1203.3519."},{"key":"e_1_3_4_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/PMBS54543.2021.00017"},{"key":"e_1_3_4_52_1","doi-asserted-by":"publisher","DOI":"10.1137\/19M1288462"},{"key":"e_1_3_4_53_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1998.10474094"},{"key":"e_1_3_4_54_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13755-017-0023-z"},{"key":"e_1_3_4_55_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-60652-9"},{"key":"e_1_3_4_56_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2019.1638834"}],"container-title":["Journal of Computational and Graphical Statistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/10618600.2024.2308216","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T01:36:56Z","timestamp":1727228216000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/10618600.2024.2308216"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,8]]},"references-count":55,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,7,2]]}},"alternative-id":["10.1080\/10618600.2024.2308216"],"URL":"https:\/\/doi.org\/10.1080\/10618600.2024.2308216","relation":{},"ISSN":["1061-8600","1537-2715"],"issn-type":[{"value":"1061-8600","type":"print"},{"value":"1537-2715","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,8]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=ucgs20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=ucgs20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2022-10-30","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-01-15","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-03-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}