{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T05:53:33Z","timestamp":1783749213578,"version":"3.55.0"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030581114","type":"print"},{"value":"9783030581121","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-58112-1_50","type":"book-chapter","created":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T16:04:30Z","timestamp":1599062670000},"page":"719-731","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Adaptive Stochastic Natural Gradient Method for Optimizing Functions with Low Effective Dimensionality"],"prefix":"10.1007","author":[{"given":"Teppei","family":"Yamaguchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kento","family":"Uchida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinichi","family":"Shirakawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,8,31]]},"reference":[{"key":"50_CR1","unstructured":"Akimoto, Y., Shirakawa, S., Yoshinari, N., Uchida, K., Saito, S., Nishida, K.: Adaptive stochastic natural gradient method for one-shot neural architecture search. In: Proceedings of the 36th International Conference on Machine Learning (ICML), pp. 171\u2013180 (2019)"},{"key":"50_CR2","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1162\/089976698300017746","volume":"10","author":"S Amari","year":"1998","unstructured":"Amari, S.: Natural gradient works efficiently in learning. Neural Comput. 10, 251\u2013276 (1998)","journal-title":"Neural Comput."},{"key":"50_CR3","doi-asserted-by":"crossref","unstructured":"Baluja, S., Caruana, R.: Removing the genetics from the standard genetic algorithm. In: Proceedings of the 12th International Conference on Machine Learning (ICML), pp. 38\u201346 (1995)","DOI":"10.1016\/B978-1-55860-377-6.50014-1"},{"key":"50_CR4","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra, J., Bengio, Y.: Random search for hyper-parameter optimization. J. Mach. Learn. Res. 13, 281\u2013305 (2012)","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"50_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/106365603321828970","volume":"11","author":"N Hansen","year":"2003","unstructured":"Hansen, N., M\u00fcller, S.D., Koumoutsakos, P.: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evol. Comput. 11(1), 1\u201318 (2003)","journal-title":"Evol. Comput."},{"key":"50_CR6","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1109\/4235.797971","volume":"3","author":"GR Harik","year":"1999","unstructured":"Harik, G.R., Lobo, F.G., Goldberg, D.E.: The compact genetic algorithm. IEEE Trans. Evol. Comput. 3, 287\u2013297 (1999)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"50_CR7","unstructured":"Hutter, F., Hoos, H., Leyton-Brown, K.: An efficient approach for assessing hyperparameter importance. In: Proceedings of the 31st International Conference on Machine Learning (ICML), pp. 754\u2013762 (2014)"},{"key":"50_CR8","doi-asserted-by":"crossref","unstructured":"Lukaczyk, T., Constantine, P., Palacios, F., Alonso, J.: Active subspaces for shape optimization. In: Proceedings of the 10th AIAA Multidisciplinary Design Optimization Conference, pp. 1\u201318 (2014)","DOI":"10.2514\/6.2014-1171"},{"key":"50_CR9","first-page":"1","volume":"18","author":"Y Ollivier","year":"2017","unstructured":"Ollivier, Y., Arnold, L., Auger, A., Hansen, N.: Information-geometric optimization algorithms: a unifying picture via invariance principles. J. Mach. Learn. Res. 18, 1\u201365 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"50_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1007\/978-3-319-45823-6_80","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XIV","author":"ML Sanyang","year":"2016","unstructured":"Sanyang, M.L., Kab\u00e1n, A.: REMEDA: random embedding EDA for optimising functions with intrinsic dimension. In: Handl, J., Hart, E., Lewis, P.R., L\u00f3pez-Ib\u00e1\u00f1ez, M., Ochoa, G., Paechter, B. (eds.) PPSN 2016. LNCS, vol. 9921, pp. 859\u2013868. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-45823-6_80"},{"key":"50_CR11","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1613\/jair.4806","volume":"55","author":"Z Wang","year":"2016","unstructured":"Wang, Z., Hutter, F., Zoghi, M., Matheson, D., de Freitas, N.: Bayesian optimization in a billion dimensions via random embeddings. J. Artif. Intell. Res. 55, 361\u2013387 (2016)","journal-title":"J. Artif. Intell. Res."},{"key":"50_CR12","first-page":"949","volume":"15","author":"D Wierstra","year":"2014","unstructured":"Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J., Schmidhuber, J.: Natural evolution strategies. J. Mach. Learn. Res. 15, 949\u2013980 (2014)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Lecture Notes in Computer Science","Parallel Problem Solving from Nature \u2013 PPSN XVI"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58112-1_50","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T16:20:53Z","timestamp":1599063653000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-58112-1_50"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030581114","9783030581121"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58112-1_50","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"31 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PPSN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Parallel Problem Solving from Nature","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Leiden","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ppsn2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ppsn2020.liacs.leidenuniv.nl\/","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":"268","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":"99","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":"37% - 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","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":"2.2","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)"}}]}}