{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T06:34:09Z","timestamp":1777358049828,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"DARPA","award":["#FA8750-17- 2-0116"],"award-info":[{"award-number":["#FA8750-17- 2-0116"]}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["#IIS-1750074"],"award-info":[{"award-number":["#IIS-1750074"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["#IIS-1718840"],"award-info":[{"award-number":["#IIS-1718840"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330648","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"1946-1956","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":623,"title":["Auto-Keras: An Efficient Neural Architecture Search System"],"prefix":"10.1145","author":[{"given":"Haifeng","family":"Jin","sequence":"first","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}]},{"given":"Qingquan","family":"Song","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}]},{"given":"Xia","family":"Hu","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013689704352"},{"key":"e_1_3_2_2_2_1","volume-title":"Designing neural network architectures using reinforcement learning. arXiv preprint arXiv:1611.02167","author":"Baker Bowen","year":"2016"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.25080\/Majora-8b375195-003"},{"key":"e_1_3_2_2_4_1","volume-title":"On Lipschitz embedding of finite metric spaces in Hilbert space. Israel Journal of Mathematics","author":"Bourgain Jean","year":"1985"},{"key":"e_1_3_2_2_5_1","volume-title":"SMASH: one-shot model architecture search through hypernetworks. arXiv preprint arXiv:1708.05344","author":"Brock Andrew","year":"2017"},{"key":"e_1_3_2_2_6_1","volume-title":"ECML PKDD Workshop: Languages for Data Mining and Machine Learning .","author":"Buitinck Lars","year":"2013"},{"key":"e_1_3_2_2_7_1","volume-title":"AAAI Conference on Artificial Intelligence .","author":"Cai Han","year":"2018"},{"key":"e_1_3_2_2_8_1","volume-title":"International Conference on Learning Representations .","author":"Cai Han","year":"2019"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2012.6364125"},{"key":"e_1_3_2_2_10_1","volume-title":"Net2net: Accelerating learning via knowledge transfer. arXiv preprint arXiv:1511.05641","author":"Chen Tianqi","year":"2015"},{"key":"e_1_3_2_2_11_1","volume-title":"mbox","author":"Franccois Chollet","year":"2015"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3067695.3076002"},{"key":"e_1_3_2_2_13_1","volume-title":"Simple And Efficient Architecture Search for Convolutional Neural Networks. arXiv preprint arXiv:1711.04528","author":"Elsken Thomas","year":"2017"},{"key":"e_1_3_2_2_14_1","volume-title":"Jan Hendrik Metzen, and Frank Hutter","author":"Elsken Thomas","year":"2018"},{"key":"e_1_3_2_2_15_1","unstructured":"Matthias Feurer Aaron Klein Katharina Eggensperger Jost Springenberg Manuel Blum and Frank Hutter. 2015. Efficient and robust automated machine learning. In Advances in Neural Information Processing Systems .   Matthias Feurer Aaron Klein Katharina Eggensperger Jost Springenberg Manuel Blum and Frank Hutter. 2015. Efficient and robust automated machine learning. In Advances in Neural Information Processing Systems ."},{"key":"e_1_3_2_2_16_1","volume-title":"NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection. arXiv preprint arXiv:1904.07392","author":"Ghiasi Golnaz","year":"2019"},{"key":"e_1_3_2_2_17_1","volume-title":"Single Path One-Shot Neural Architecture Search with Uniform Sampling. arXiv preprint arXiv:1904.00420","author":"Guo Zichao","year":"2019"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-28649-3_27"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSSC.1968.300136"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013878"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25566-3_40"},{"key":"e_1_3_2_2_22_1","volume-title":"Neural Architecture Search with Bayesian Optimisation and Optimal Transport. Advances in Neural Information Processing Systems","author":"Kandasamy Kirthevasan","year":"2018"},{"key":"e_1_3_2_2_23_1","volume-title":"Optimization by simulated annealing. science","author":"Kirkpatrick Scott","year":"1983"},{"key":"e_1_3_2_2_24_1","volume-title":"Automatic model selection and hyperparameter optimization in WEKA. Journal of Machine Learning Research","author":"Kotthoff Lars","year":"2016"},{"key":"e_1_3_2_2_26_1","volume-title":"The Hungarian method for the assignment problem. Naval Research Logistics","author":"Kuhn Harold W","year":"1955"},{"key":"e_1_3_2_2_27_1","volume-title":"Gradient-based learning applied to document recognition. Proc","author":"LeCun Yann","year":"1998"},{"key":"e_1_3_2_2_28_1","volume-title":"Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation. arXiv preprint arXiv:1901.02985","author":"Liu Chenxi","year":"2019"},{"key":"e_1_3_2_2_29_1","volume-title":"European Conference on Computer Vision .","author":"Liu Chenxi","year":"2017"},{"key":"e_1_3_2_2_30_1","volume-title":"Hierarchical representations for efficient architecture search. arXiv preprint arXiv:1711.00436","author":"Liu Hanxiao","year":"2017"},{"key":"e_1_3_2_2_31_1","volume-title":"Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055","author":"Liu Hanxiao","year":"2018"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"e_1_3_2_2_33_1","unstructured":"Renqian Luo Fei Tian Tao Qin Enhong Chen and Tie-Yan Liu. 2018. Neural architecture optimization. In Advances in Neural Information Processing Systems .   Renqian Luo Fei Tian Tao Qin Enhong Chen and Tie-Yan Liu. 2018. Neural architecture optimization. In Advances in Neural Information Processing Systems ."},{"key":"e_1_3_2_2_34_1","volume-title":"Euclidean embeddings of finite metric spaces. Discrete Mathematics","author":"Maehara Hiroshi","year":"2013"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2908812.2908918"},{"key":"e_1_3_2_2_36_1","volume-title":"et almbox","author":"Pedregosa Fabian","year":"2011"},{"key":"e_1_3_2_2_37_1","volume-title":"Efficient Neural Architecture Search via Parameter Sharing. arXiv preprint arXiv:1802.03268","author":"Pham Hieu","year":"2018"},{"key":"e_1_3_2_2_38_1","volume-title":"Regularized Evolution for Image Classifier Architecture Search. arXiv preprint arXiv:1802.01548","author":"Real Esteban","year":"2018"},{"key":"e_1_3_2_2_39_1","volume-title":"International Conference on Machine Learning. arXiv preprint arXiv:1703","author":"Real Esteban","year":"2017"},{"key":"e_1_3_2_2_40_1","unstructured":"Jasper Snoek Hugo Larochelle and Ryan P Adams. 2012. Practical bayesian optimization of machine learning algorithms. In Advances in Neural Information Processing Systems .   Jasper Snoek Hugo Larochelle and Ryan P Adams. 2012. Practical bayesian optimization of machine learning algorithms. In Advances in Neural Information Processing Systems ."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071229"},{"key":"e_1_3_2_2_42_1","volume-title":"Mnasnet: Platform-aware neural architecture search for mobile. arXiv preprint arXiv:1807.11626","author":"Tan Mingxing","year":"2018"},{"key":"e_1_3_2_2_43_1","volume-title":"Deep Representation Learning for Social Network Analysis. arXiv preprint arXiv:1904.08547","author":"Tan Qiaoyu","year":"2019"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487629"},{"key":"e_1_3_2_2_45_1","volume-title":"International Conference on Machine Learning .","author":"Wei Tao","year":"2016"},{"key":"e_1_3_2_2_46_1","unstructured":"Han Xiao Kashif Rasul and Roland Vollgraf. 2017. Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms. showeprint{arXiv}cs.LG\/cs.LG\/1708.07747  Han Xiao Kashif Rasul and Roland Vollgraf. 2017. Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms. showeprint{arXiv}cs.LG\/cs.LG\/1708.07747"},{"key":"e_1_3_2_2_47_1","volume-title":"International Conference on Learning Representations .","author":"Xie Sirui","year":"2019"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783417"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687631"},{"key":"e_1_3_2_2_50_1","volume-title":"Practical Network Blocks Design with Q-Learning. arXiv preprint arXiv:1708.05552","author":"Zhong Zhao","year":"2017"},{"key":"e_1_3_2_2_51_1","volume-title":"International Conference on Learning Representations .","author":"Zoph Barret","year":"2016"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Anchorage AK USA","acronym":"KDD '19","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330648","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330648","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330648","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:02:09Z","timestamp":1750208529000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330648"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":50,"alternative-id":["10.1145\/3292500.3330648","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330648","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}