{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T19:53:08Z","timestamp":1729626788224,"version":"3.28.0"},"reference-count":26,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,10]]},"DOI":"10.1109\/iccabs.2017.8114299","type":"proceedings-article","created":{"date-parts":[[2017,11,20]],"date-time":"2017-11-20T16:34:24Z","timestamp":1511195664000},"page":"1-6","source":"Crossref","is-referenced-by-count":12,"title":["Efficient hyperparameter optimization by using Bayesian optimization for drug-target interaction prediction"],"prefix":"10.1109","author":[{"given":"Tomohiro","family":"Ban","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masahito","family":"Ohue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yutaka","family":"Akiyama","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2011.2182033"},{"key":"ref11","first-page":"ii-253","article-title":"Gaussian process optimization with mutual information","volume":"32","author":"contal","year":"2014","journal-title":"Proc 31st Int Conf Machine Learning (ICML-14)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2494218"},{"key":"ref13","first-page":"2249","article-title":"An empirical evaluation of Thompson sampling","volume":"24","author":"chapelle","year":"2011","journal-title":"Adv in Neural Inform Process Syst (NIPS)"},{"key":"ref14","first-page":"944","article-title":"Au-tomatic gait optimization with Gaussian process regression","volume":"7","author":"lizotte","year":"2007","journal-title":"Proc 20th Int Joint Conf Artif Intell"},{"key":"ref15","article-title":"Automatic chemical design using a data-driven continuous representation of molecules","author":"g\u00f3mez-bombarelli","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkj102"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkh081"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"919d","DOI":"10.1093\/nar\/gkm862","article-title":"SuperTarget and Matador: Resources for exploring drug-target relationships","volume":"36","author":"g\u00fcnther","year":"2008","journal-title":"Nucleic Acids Res"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkm958"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts670"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0066952"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1021\/ci400219z"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts360"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1004760"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487670"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btn162"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008306431147"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt1338"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1021\/ja036030u"},{"key":"ref22","first-page":"2121","article-title":"Adaptive subgradient methods for online learning and stochastic optimization","volume":"12","author":"duchi","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref21","article-title":"Logistic matrix factorization for implicit feedback data","author":"johnson","year":"2014","journal-title":"NIPS Workshop on Distributed Machine Learning and Matrix Computations"},{"journal-title":"Statistical Power Analysis for the Behavioral Sciences","year":"1988","author":"cohen","key":"ref24"},{"journal-title":"Gaussian Processes for Machine Learning","year":"2006","author":"rasmussen","key":"ref23"},{"key":"ref26","article-title":"Practical Bayesian optimization of machine learning algorithms","volume":"25","author":"snoek","year":"2012","journal-title":"Adv in Neural Inform Process Syst (NIPS)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.22237\/jmasm\/1257035100"}],"event":{"name":"2017 IEEE 7th International Conference on Computational Advances in Bio- and Medical Sciences (ICCABS)","start":{"date-parts":[[2017,10,19]]},"location":"Orlando, FL","end":{"date-parts":[[2017,10,21]]}},"container-title":["2017 IEEE 7th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8104489\/8114282\/08114299.pdf?arnumber=8114299","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,6]],"date-time":"2019-10-06T06:54:56Z","timestamp":1570344896000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8114299\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/iccabs.2017.8114299","relation":{},"subject":[],"published":{"date-parts":[[2017,10]]}}}