{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:56:59Z","timestamp":1784739419025,"version":"3.55.0"},"reference-count":15,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,5]]},"DOI":"10.1109\/ijcnn.2017.7965867","type":"proceedings-article","created":{"date-parts":[[2017,7,10]],"date-time":"2017-07-10T17:41:30Z","timestamp":1499708490000},"page":"286-293","source":"Crossref","is-referenced-by-count":21,"title":["Bayesian optimization for conditional hyperparameter spaces"],"prefix":"10.1109","author":[{"given":"Julien-Charles","family":"Levesque","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Audrey","family":"Durand","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Gagne","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Sabourin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","author":"klein","year":"2016","journal-title":"Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets"},{"key":"ref11","article-title":"Predictive Entropy Search for Efficient Global Optimization of Black-box Functions","author":"hern\u00e1ndez-lobato","year":"2014","journal-title":"Proceedings of NIPS"},{"key":"ref12","article-title":"Mondrian Forests: Efficient Online Random Forests","author":"lakshminarayanan","year":"2014","journal-title":"Proceedings of NIPS"},{"key":"ref13","article-title":"The Mondrian Kernel","author":"balog","year":"2016","journal-title":"Proceedings of the 32nd Conference"},{"key":"ref14","article-title":"Mondrian Forests for Large-Scale Regression when Uncertainty Matters","author":"lakshminarayanan","year":"2016","journal-title":"Proceedings of the 19th AISTATS"},{"key":"ref15","article-title":"The CMA evolution strategy: A tutorial","author":"hansen","year":"2005","journal-title":"Tech Rep"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/978-3-642-25566-3_40","article-title":"Sequen-tial Model-Based Optimization for General Algorithm Configuration","author":"hutter","year":"2011","journal-title":"Learning and Intelligent Optimization"},{"key":"ref3","article-title":"Efficient and Robust Automated Machine Learning","author":"feurer","year":"2015","journal-title":"Proceedings of NIPS"},{"key":"ref6","article-title":"Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters","author":"eggensperger","year":"2013","journal-title":"NIPS Workshop on Bayesian Optimization in Theory and Practice"},{"key":"ref5","article-title":"On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning","author":"hoffman","year":"2014","journal-title":"Proceedings of the 17th AISTATS"},{"key":"ref8","article-title":"Slice Sampling Covariance Hyperparameters of Latent Gaussian Models","author":"murray","year":"2010","journal-title":"Proceedings of NIPS"},{"key":"ref7","article-title":"Practical Bayesian Optimization of Machine Learning Algorithms","author":"snoek","year":"2012","journal-title":"Proceedings of NIPS"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487629"},{"key":"ref1","first-page":"2546","article-title":"Algorithms for Hyper-Parameter Optimization","author":"bergstra","year":"2011","journal-title":"Proceedings of NIPS"},{"key":"ref9","author":"li","year":"2016","journal-title":"Hyperband A Novel Bandit-Based Approach to Hyperparameter Optimization"}],"event":{"name":"2017 International Joint Conference on Neural Networks (IJCNN)","location":"Anchorage, AK, USA","start":{"date-parts":[[2017,5,14]]},"end":{"date-parts":[[2017,5,19]]}},"container-title":["2017 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7958416\/7965814\/07965867.pdf?arnumber=7965867","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,29]],"date-time":"2019-09-29T06:22:15Z","timestamp":1569738135000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7965867\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5]]},"references-count":15,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2017.7965867","relation":{},"subject":[],"published":{"date-parts":[[2017,5]]}}}