{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T03:09:43Z","timestamp":1771038583800,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030352875","type":"print"},{"value":"9783030352882","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-35288-2_38","type":"book-chapter","created":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T00:02:57Z","timestamp":1574640177000},"page":"473-484","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Bayesian Optimization with Discrete Variables"],"prefix":"10.1007","author":[{"given":"Phuc","family":"Luong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunil","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dang","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Santu","family":"Rana","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Svetha","family":"Venkatesh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,11,25]]},"reference":[{"key":"38_CR1","doi-asserted-by":"crossref","unstructured":"Bergstra, J., Yamins, D., Cox, D.D.: Hyperopt: a python library for optimizing the hyperparameters of machine learning algorithms. In: Proceedings of the 12th Python in Science Conference, pp. 13\u201320. Citeseer (2013)","DOI":"10.25080\/Majora-8b375195-003"},{"key":"38_CR2","unstructured":"Bergstra, J.S., Bardenet, R., Bengio, Y., K\u00e9gl, B.: Algorithms for hyper-parameter optimization. In: Advances in Neural Information Processing Systems, pp. 2546\u20132554 (2011)"},{"key":"38_CR3","unstructured":"Brochu, E., Cora, V.M., De Freitas, N.: A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. arXiv preprint arXiv:1012.2599 (2010)"},{"key":"38_CR4","doi-asserted-by":"crossref","unstructured":"Garrido-Merch\u00e1n, E.C., Hern\u00e1ndez-Lobato, D.: Dealing with categorical and integer-valued variables in Bayesian optimization with Gaussian processes. arXiv preprint arXiv:1805.03463 (2018)","DOI":"10.1016\/j.neucom.2019.11.004"},{"key":"38_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1007\/978-3-642-25566-3_40","volume-title":"Learning and Intelligent Optimization","author":"F Hutter","year":"2011","unstructured":"Hutter, F., Hoos, H.H., Leyton-Brown, K.: Sequential model-based optimization for general algorithm configuration. In: Coello, C.A.C. (ed.) LION 2011. LNCS, vol. 6683, pp. 507\u2013523. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-25566-3_40"},{"key":"38_CR6","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1007\/978-3-642-40988-2_14","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"A Jalali","year":"2013","unstructured":"Jalali, A., Azimi, J., Fern, X., Zhang, R.: A lipschitz exploration-exploitation scheme for Bayesian optimization. In: Blockeel, H., Kersting, K., Nijssen, S., \u017delezn\u00fd, F. (eds.) ECML PKDD 2013. LNCS (LNAI), vol. 8188, pp. 210\u2013224. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40988-2_14"},{"issue":"4","key":"38_CR7","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1023\/A:1008306431147","volume":"13","author":"DR Jones","year":"1998","unstructured":"Jones, D.R., Schonlau, M., Welch, W.J.: Efficient global optimization of expensive black-box functions. J. Glob. Optim. 13(4), 455\u2013492 (1998)","journal-title":"J. Glob. Optim."},{"issue":"1","key":"38_CR8","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1115\/1.3653121","volume":"86","author":"HJ Kushner","year":"1964","unstructured":"Kushner, H.J.: A new method of locating the maximum point of an arbitrary multipeak curve in the presence of noise. J. Basic Eng. 86(1), 97\u2013106 (1964)","journal-title":"J. Basic Eng."},{"key":"38_CR9","unstructured":"Lakshminarayanan, B., Roy, D.M., Teh, Y.W.: Mondrian forests for large-scale regression when uncertainty matters. In: Artificial Intelligence and Statistics, pp. 1478\u20131487 (2016)"},{"key":"38_CR10","unstructured":"Lizotte, D.J.: Practical Bayesian optimization. University of Alberta (2008)"},{"issue":"4","key":"38_CR11","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1007\/BF01099263","volume":"4","author":"J Mockus","year":"1994","unstructured":"Mockus, J.: Application of Bayesian approach to numerical methods of global and stochastic optimization. J. Glob. Optim. 4(4), 347\u2013365 (1994)","journal-title":"J. Glob. Optim."},{"issue":"117\u2013129","key":"38_CR12","first-page":"2","volume":"2","author":"J Mockus","year":"1978","unstructured":"Mockus, J., Tiesis, V., Zilinskas, A.: The application of Bayesian methods for seeking the extremum. Towards Glob. Optim. 2(117\u2013129), 2 (1978)","journal-title":"Towards Glob. Optim."},{"key":"38_CR13","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/978-3-540-28650-9_4","volume-title":"Advanced Lectures on Machine Learning","author":"CE Rasmussen","year":"2004","unstructured":"Rasmussen, C.E.: Gaussian processes in machine learning. In: Bousquet, O., von Luxburg, U., R\u00e4tsch, G. (eds.) ML 2003. LNCS (LNAI), vol. 3176, pp. 63\u201371. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-28650-9_4"},{"key":"38_CR14","unstructured":"Reyes-Ortiz, J.L., Anguita, D., Ghio, A., Parra, X.: Human activity recognition using smartphones data set. UCI Machine Learning Repository; University of California, Irvine, School of Information and Computer Sciences: Irvine, CA, USA (2012)"},{"issue":"1","key":"38_CR15","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1109\/JPROC.2015.2494218","volume":"104","author":"B Shahriari","year":"2016","unstructured":"Shahriari, B., Swersky, K., Wang, Z., Adams, R.P., De Freitas, N.: Taking the human out of the loop: a review of Bayesian optimization. Proc. IEEE 104(1), 148\u2013175 (2016)","journal-title":"Proc. IEEE"},{"issue":"5","key":"38_CR16","doi-asserted-by":"publisher","first-page":"3250","DOI":"10.1109\/TIT.2011.2182033","volume":"58","author":"N Srinivas","year":"2012","unstructured":"Srinivas, N., Krause, A., Kakade, S.M., Seeger, M.W.: Information-theoretic regret bounds for Gaussian process optimization in the bandit setting. IEEE Trans. Inform. Theory 58(5), 3250\u20133265 (2012)","journal-title":"IEEE Trans. Inform. Theory"},{"issue":"3","key":"38_CR17","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1109\/21.155943","volume":"22","author":"L Xu","year":"1992","unstructured":"Xu, L., Krzyzak, A., Suen, C.Y.: Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans. Syst. Man Cybern. 22(3), 418\u2013435 (1992)","journal-title":"IEEE Trans. Syst. Man Cybern."}],"container-title":["Lecture Notes in Computer Science","AI 2019: Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-35288-2_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,5]],"date-time":"2021-02-05T23:09:25Z","timestamp":1612566565000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-35288-2_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030352875","9783030352882"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-35288-2_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"25 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australasian Joint Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Adelaide, SA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ausai2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/nugget.unisa.edu.au\/AI2019\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"115","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"42% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}