{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T13:22:53Z","timestamp":1725024173566},"reference-count":26,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-009"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-001"}],"funder":[{"DOI":"10.13039\/501100018795","name":"Instituto Nacional de Astrof\u00edsica, \u00d3ptica y Electr\u00f3nica","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100018795","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CONACyT-Mexico","award":["CB-A1-S-26314"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2021,9,1]]},"DOI":"10.1109\/tpami.2021.3077106","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T20:27:36Z","timestamp":1628108856000},"page":"2887-2890","source":"Crossref","is-referenced-by-count":7,"title":["Guest Editorial: Automated Machine Learning"],"prefix":"10.1109","volume":"43","author":[{"given":"Hugo Jair","family":"Escalante","sequence":"first","affiliation":[]},{"given":"Quanming","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Wei-Wei","family":"Tu","sequence":"additional","affiliation":[]},{"given":"Nelishia","family":"Pillay","sequence":"additional","affiliation":[]},{"given":"Rong","family":"Qu","sequence":"additional","affiliation":[]},{"given":"Yang","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Neil","family":"Houlsby","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"crossref","article-title":"Automated Machine Learning - A Brief Review at the End of the Early Years","author":"escalante","year":"2021","DOI":"10.1007\/978-3-030-72069-8_2"},{"key":"ref11","article-title":"You only search once: Single shot neural architecture search via direct sparse optimization","author":"zhang","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3020315"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3035351"},{"key":"ref14","article-title":"MIGO-NAS: Towards fast and generalizable neural architecture search","author":"zheng","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref15","article-title":"Partially-connected neural architecture search for reduced computational redundancy","author":"xu","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref16","article-title":"Neural architecture transfer","author":"lu","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref17","article-title":"FNA++: Fast network adaptation via parameter remapping and architecture search","author":"fang","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3036338"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3026019"},{"key":"ref4","article-title":"Taking human out of learning applications: A survey on automated machine learning","author":"yao","year":"2018"},{"key":"ref3","article-title":"The algorithm selection problem,” in ”Computer Science Technical Reports. Paper 99","author":"rice","year":"1975"},{"key":"ref6","article-title":"AutoML: A survey of the state-of-the-art","author":"he","year":"2019"},{"key":"ref5","article-title":"Survey on automated machine learning","author":"z\u00f6ller","year":"2019"},{"key":"ref8","article-title":"Neural architecture search: A survey","author":"elsken","year":"2018"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/SDS.2019.00-11"},{"key":"ref2","article-title":"Overview and unifying conceptualization of automated machine learning","author":"liu","year":"2019","journal-title":"Proc Automat Data Sci Workshop"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2018.2806988"},{"key":"ref1","doi-asserted-by":"crossref","author":"hutter","year":"2019","journal-title":"Automated Machine Learning Methods Systems Challenges The Springer Series on Challenges in Machine Learning","DOI":"10.1007\/978-3-030-05318-5"},{"key":"ref20","article-title":"AutoML for multi-label classification: Overview and empirical evaluation","author":"wever","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref22","article-title":"Adaptation strategies for automated machine learning on evolving data","author":"celik","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref21","article-title":"Predicting machine learning pipeline runtimes in the context of automated machine learning","author":"mohr","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref24","article-title":"Evolving fully automated machine learning via life-long knowledge anchors","author":"tangy","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref23","article-title":"Auto-Pytorch: multi-fidelity metalearning for efficient and robust autoDL","author":"zimmer","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref26","article-title":"Darts: Differentiable architecture search","author":"liu","year":"2019"},{"key":"ref25","article-title":"Winning solutions and post-challenge analyses of the chalearn autoDL challenge 2019","author":"liu","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/9506969\/09506965.pdf?arnumber=9506965","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T15:08:25Z","timestamp":1673017705000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9506965\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,1]]},"references-count":26,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2021.3077106","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,1]]}}}