{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:03:14Z","timestamp":1775325794590,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","award":["W911NF-16-1-0565, FA8750-17-2-0116"],"award-info":[{"award-number":["W911NF-16-1-0565, FA8750-17-2-0116"]}],"id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-1657196, IIS-1718840"],"award-info":[{"award-number":["IIS-1657196, 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":[[2020,8,23]]},"DOI":"10.1145\/3394486.3403137","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T23:04:00Z","timestamp":1597964640000},"page":"945-955","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":62,"title":["Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction"],"prefix":"10.1145","author":[{"given":"Qingquan","family":"Song","sequence":"first","affiliation":[{"name":"Texas A&amp;M University, College Station, TX, USA"}]},{"given":"Dehua","family":"Cheng","sequence":"additional","affiliation":[{"name":"Facebook Inc., Menlo Park, CA, USA"}]},{"given":"Hanning","family":"Zhou","sequence":"additional","affiliation":[{"name":"Facebook Inc., Menlo Park, CA, USA"}]},{"given":"Jiyan","family":"Yang","sequence":"additional","affiliation":[{"name":"Facebook Inc., Menlo Park, CA, USA"}]},{"given":"Yuandong","family":"Tian","sequence":"additional","affiliation":[{"name":"Facebook Inc, Menlo Park, CA, USA"}]},{"given":"Xia","family":"Hu","sequence":"additional","affiliation":[{"name":"Facebook Inc., Menlo Park, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Thomas Back. 1994. Selective pressure in evolutionary algorithms: A characterization of selection mechanisms. In WCCI.  Thomas Back. 1994. Selective pressure in evolutionary algorithms: A characterization of selection mechanisms. In WCCI."},{"key":"e_1_3_2_2_2_1","volume-title":"A comparison of selection schemes used in evolutionary algorithms. Evolutionary Computation","author":"Blickle Tobias","year":"1996","unstructured":"Tobias Blickle and Lothar Thiele . 1996. A comparison of selection schemes used in evolutionary algorithms. Evolutionary Computation ( 1996 ). Tobias Blickle and Lothar Thiele. 1996. A comparison of selection schemes used in evolutionary algorithms. Evolutionary Computation (1996)."},{"key":"e_1_3_2_2_3_1","volume-title":"From ranknet to lambdarank to lambdamart: An overview. Learning","author":"Burges Christopher JC","year":"2010","unstructured":"Christopher JC Burges . 2010. From ranknet to lambdarank to lambdamart: An overview. Learning ( 2010 ). Christopher JC Burges. 2010. From ranknet to lambdarank to lambdamart: An overview. Learning (2010)."},{"key":"e_1_3_2_2_4_1","unstructured":"Guillaume MJ-B Chaslot Mark HM Winands and H Jaap van Den Herik. [n.d.]. Parallel monte-carlo tree search. In ICCG.  Guillaume MJ-B Chaslot Mark HM Winands and H Jaap van Den Herik. [n.d.]. Parallel monte-carlo tree search. In ICCG."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"crossref","unstructured":"Yukang Chen Gaofeng Meng Qian Zhang Shiming Xiang Chang Huang Lisen Mu and Xinggang Wang. 2019 a. RENAS: Reinforced Evolutionary Neural Architecture Search. In CVPR.  Yukang Chen Gaofeng Meng Qian Zhang Shiming Xiang Chang Huang Lisen Mu and Xinggang Wang. 2019 a. RENAS: Reinforced Evolutionary Neural Architecture Search. In CVPR.","DOI":"10.1109\/CVPR.2019.00492"},{"key":"e_1_3_2_2_6_1","volume-title":"2019 b. Techniques for Automated Machine Learning. arXiv preprint arXiv:1907.08908","author":"Chen Yi-Wei","year":"2019","unstructured":"Yi-Wei Chen , Qingquan Song , and Xia Hu . 2019 b. Techniques for Automated Machine Learning. arXiv preprint arXiv:1907.08908 ( 2019 ). Yi-Wei Chen, Qingquan Song, and Xia Hu. 2019 b. Techniques for Automated Machine Learning. arXiv preprint arXiv:1907.08908 (2019)."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_8_1","volume-title":"Jan Hendrik Metzen, and Frank Hutter","author":"Elsken Thomas","year":"2019","unstructured":"Thomas Elsken , Jan Hendrik Metzen, and Frank Hutter . 2019 . Neural Architecture Search: A Survey. JMLR ( 2019). Thomas Elsken, Jan Hendrik Metzen, and Frank Hutter. 2019. Neural Architecture Search: A Survey. JMLR (2019)."},{"key":"e_1_3_2_2_9_1","unstructured":"Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: a factorization-machine based neural network for CTR prediction. In IJCAI.  Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: a factorization-machine based neural network for CTR prediction. In IJCAI."},{"key":"e_1_3_2_2_10_1","unstructured":"Xiangnan He and Tat-Seng Chua. 2017. Neural factorization machines for sparse predictive analytics. In SIGIR.  Xiangnan He and Tat-Seng Chua. 2017. Neural factorization machines for sparse predictive analytics. In SIGIR."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2648584.2648589"},{"key":"e_1_3_2_2_12_1","volume-title":"Neural Architecture Refinement: A Practical Way for Avoiding Overfitting in NAS. arXiv:1905.02341","author":"Jiang Yang","year":"2019","unstructured":"Yang Jiang , Cong Zhao , and Lei Pang . 2019. Neural Architecture Refinement: A Practical Way for Avoiding Overfitting in NAS. arXiv:1905.02341 ( 2019 ). Yang Jiang, Cong Zhao, and Lei Pang. 2019. Neural Architecture Refinement: A Practical Way for Avoiding Overfitting in NAS. arXiv:1905.02341 (2019)."},{"key":"e_1_3_2_2_13_1","volume-title":"Auto-keras: An efficient neural architecture search system. In SIGKDD.","author":"Jin Haifeng","year":"2019","unstructured":"Haifeng Jin , Qingquan Song , and Xia Hu . 2019 . Auto-keras: An efficient neural architecture search system. In SIGKDD. Haifeng Jin, Qingquan Song, and Xia Hu. 2019. Auto-keras: An efficient neural architecture search system. In SIGKDD."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"crossref","unstructured":"Yuchin Juan Yong Zhuang Wei-Sheng Chin and Chih-Jen Lin. 2016. Field-aware factorization machines for CTR prediction. In RecSys.  Yuchin Juan Yong Zhuang Wei-Sheng Chin and Chih-Jen Lin. 2016. Field-aware factorization machines for CTR prediction. In RecSys.","DOI":"10.1145\/2959100.2959134"},{"key":"e_1_3_2_2_15_1","volume-title":"Random search and reproducibility for neural architecture search. arXiv:1902.07638","author":"Li Liam","year":"2019","unstructured":"Liam Li and Ameet Talwalkar . 2019. Random search and reproducibility for neural architecture search. arXiv:1902.07638 ( 2019 ). Liam Li and Ameet Talwalkar. 2019. Random search and reproducibility for neural architecture search. arXiv:1902.07638 (2019)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Jianxun Lian Xiaohuan Zhou Fuzheng Zhang Zhongxia Chen Xing Xie and Guangzhong Sun. 2018. xdeepfm: Combining explicit and implicit feature interactions for recommender systems. In SIGKDD.  Jianxun Lian Xiaohuan Zhou Fuzheng Zhang Zhongxia Chen Xing Xie and Guangzhong Sun. 2018. xdeepfm: Combining explicit and implicit feature interactions for recommender systems. In SIGKDD.","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_2_17_1","unstructured":"Chenxi Liu Liang-Chieh Chen Florian Schroff Hartwig Adam Wei Hua Alan Yuille and Fei-Fei Li. 2019 a. Auto-deeplab: Hierarchical Neural Architecture Search for Semantic Image Segmentation. In CVPR.  Chenxi Liu Liang-Chieh Chen Florian Schroff Hartwig Adam Wei Hua Alan Yuille and Fei-Fei Li. 2019 a. Auto-deeplab: Hierarchical Neural Architecture Search for Semantic Image Segmentation. In CVPR."},{"key":"e_1_3_2_2_18_1","unstructured":"Hanxiao Liu Karen Simonyan and Yiming Yang. 2019 b. DARTS: Differentiable Architecture Search. In ICLR.  Hanxiao Liu Karen Simonyan and Yiming Yang. 2019 b. DARTS: Differentiable Architecture Search. In ICLR."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"crossref","unstructured":"Qiang Liu Feng Yu Shu Wu and Liang Wang. 2015. A convolutional click prediction model. In CIKM.  Qiang Liu Feng Yu Shu Wu and Liang Wang. 2015. A convolutional click prediction model. In CIKM.","DOI":"10.1145\/2806416.2806603"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"crossref","unstructured":"H Brendan McMahan Gary Holt David Sculley Michael Young Dietmar Ebner Julian Grady Lan Nie Todd Phillips Eugene Davydov Daniel Golovin etal 2013. Ad click prediction: a view from the trenches. In SIGKDD.  H Brendan McMahan Gary Holt David Sculley Michael Young Dietmar Ebner Julian Grady Lan Nie Todd Phillips Eugene Davydov Daniel Golovin et al. 2013. Ad click prediction: a view from the trenches. In SIGKDD.","DOI":"10.1145\/2487575.2488200"},{"key":"e_1_3_2_2_21_1","volume-title":"Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G Azzolini, et al.","author":"Naumov Maxim","year":"2019","unstructured":"Maxim Naumov , Dheevatsa Mudigere , Hao-Jun Michael Shi , Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G Azzolini, et al. 2019 . Deep Learning Recommendation Model for Personalization and Recommendation Systems . arXiv:1906.00091 (2019). Maxim Naumov, Dheevatsa Mudigere, Hao-Jun Michael Shi, Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G Azzolini, et al. 2019. Deep Learning Recommendation Model for Personalization and Recommendation Systems. arXiv:1906.00091 (2019)."},{"key":"e_1_3_2_2_22_1","unstructured":"Hieu Pham Melody Guan Barret Zoph Quoc Le and Jeff Dean. 2018. Efficient Neural Architecture Search via Parameters Sharing. In ICML.  Hieu Pham Melody Guan Barret Zoph Quoc Le and Jeff Dean. 2018. Efficient Neural Architecture Search via Parameters Sharing. In ICML."},{"key":"e_1_3_2_2_23_1","unstructured":"Yanru Qu Han Cai Kan Ren Weinan Zhang Yong Yu Ying Wen and Jun Wang. 2016. Product-based neural networks for user response prediction. In ICDM.  Yanru Qu Han Cai Kan Ren Weinan Zhang Yong Yu Ying Wen and Jun Wang. 2016. Product-based neural networks for user response prediction. In ICDM."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"crossref","unstructured":"Esteban Real Alok Aggarwal Yanping Huang and Quoc V Le. 2019. Regularized evolution for image classifier architecture search. In AAAI.  Esteban Real Alok Aggarwal Yanping Huang and Quoc V Le. 2019. Regularized evolution for image classifier architecture search. In AAAI.","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"e_1_3_2_2_25_1","volume-title":"Jie Tan, Quoc V. Le, and Alexey Kurakin.","author":"Real Esteban","year":"2017","unstructured":"Esteban Real , Sherry Moore , Andrew Selle , Saurabh Saxena , Yutaka Leon Suematsu , Jie Tan, Quoc V. Le, and Alexey Kurakin. 2017 . Large-Scale Evolution of Image Classifiers. In ICML. Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc V. Le, and Alexey Kurakin. 2017. Large-Scale Evolution of Image Classifiers. In ICML."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Steffen Rendle. 2010. Factorization machines. In ICDM.  Steffen Rendle. 2010. Factorization machines. In ICDM.","DOI":"10.1109\/ICDM.2010.127"},{"key":"e_1_3_2_2_27_1","volume-title":"Evaluating the search phase of neural architecture search. arXiv:1902.08142","author":"Sciuto Christian","year":"2019","unstructured":"Christian Sciuto , Kaicheng Yu , Martin Jaggi , Claudiu Musat , and Mathieu Salzmann . 2019. Evaluating the search phase of neural architecture search. arXiv:1902.08142 ( 2019 ). Christian Sciuto, Kaicheng Yu, Martin Jaggi, Claudiu Musat, and Mathieu Salzmann. 2019. Evaluating the search phase of neural architecture search. arXiv:1902.08142 (2019)."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357925"},{"key":"e_1_3_2_2_29_1","volume-title":"Sample-Efficient Neural Architecture Search by Learning Action Space. arXiv:1906.06832","author":"Wang Linnan","year":"2019","unstructured":"Linnan Wang , Saining Xie , Teng Li , Rodrigo Fonseca , and Yuandong Tian . 2019. Sample-Efficient Neural Architecture Search by Learning Action Space. arXiv:1906.06832 ( 2019 ). Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, and Yuandong Tian. 2019. Sample-Efficient Neural Architecture Search by Learning Action Space. arXiv:1906.06832 (2019)."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Ruoxi Wang Bin Fu Gang Fu and Mingliang Wang. 2017. Deep & cross network for ad click predictions. In ADKDD.  Ruoxi Wang Bin Fu Gang Fu and Mingliang Wang. 2017. Deep & cross network for ad click predictions. In ADKDD.","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_2_31_1","volume-title":"Inductive Transfer for Neural Architecture Optimization. arXiv:1903.03536","author":"Wistuba Martin","year":"2019","unstructured":"Martin Wistuba and Tejaswini Pedapati . 2019. Inductive Transfer for Neural Architecture Optimization. arXiv:1903.03536 ( 2019 ). Martin Wistuba and Tejaswini Pedapati. 2019. Inductive Transfer for Neural Architecture Optimization. arXiv:1903.03536 (2019)."},{"key":"e_1_3_2_2_32_1","unstructured":"Ling Yan Wu-Jun Li Gui-Rong Xue and Dingyi Han. 2014. Coupled group lasso for web-scale ctr prediction in display advertising. In ICML.  Ling Yan Wu-Jun Li Gui-Rong Xue and Dingyi Han. 2014. Coupled group lasso for web-scale ctr prediction in display advertising. In ICML."},{"key":"e_1_3_2_2_33_1","volume-title":"Understanding and Robustifying Differentiable Architecture Search. ICLR","author":"Zela Arber","year":"2020","unstructured":"Arber Zela , Thomas Elsken , Tonmoy Saikia , Yassine Marrakchi , Thomas Brox , and Frank Hutter . 2020. Understanding and Robustifying Differentiable Architecture Search. ICLR ( 2020 ). Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, and Frank Hutter. 2020. Understanding and Robustifying Differentiable Architecture Search. ICLR (2020)."},{"key":"e_1_3_2_2_34_1","volume-title":"Comparison of selection methods for evolutionary optimization. Evolutionary Optimization","author":"Zhang Byoung-Tak","year":"2000","unstructured":"Byoung-Tak Zhang and Jung-Jib Kim . 2000. Comparison of selection methods for evolutionary optimization. Evolutionary Optimization ( 2000 ). Byoung-Tak Zhang and Jung-Jib Kim. 2000. Comparison of selection methods for evolutionary optimization. Evolutionary Optimization (2000)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Tianming Du and Jun Wang. 2016. Deep learning over multi-field categorical data. In ECIR.  Weinan Zhang Tianming Du and Jun Wang. 2016. Deep learning over multi-field categorical data. In ECIR.","DOI":"10.1007\/978-3-319-30671-1_4"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Guorui Zhou Xiaoqiang Zhu Chenru Song Ying Fan Han Zhu Xiao Ma Yanghui Yan Junqi Jin Han Li and Kun Gai. 2018. Deep interest network for click-through rate prediction. In SIGKDD.  Guorui Zhou Xiaoqiang Zhu Chenru Song Ying Fan Han Zhu Xiao Ma Yanghui Yan Junqi Jin Han Li and Kun Gai. 2018. Deep interest network for click-through rate prediction. In SIGKDD.","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_2_37_1","unstructured":"Barret Zoph and Quoc V Le. 2017. Neural architecture search with reinforcement learning. In ICLR.  Barret Zoph and Quoc V Le. 2017. Neural architecture search with reinforcement learning. In ICLR."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"crossref","unstructured":"Barret Zoph Vijay Vasudevan Jonathon Shlens and Quoc V Le. 2018. Learning transferable architectures for scalable image recognition. In CVPR.  Barret Zoph Vijay Vasudevan Jonathon Shlens and Quoc V Le. 2018. Learning transferable architectures for scalable image recognition. In CVPR.","DOI":"10.1109\/CVPR.2018.00907"}],"event":{"name":"KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event CA USA","acronym":"KDD '20","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 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403137","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394486.3403137","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394486.3403137","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:34Z","timestamp":1750195894000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403137"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,20]]},"references-count":38,"alternative-id":["10.1145\/3394486.3403137","10.1145\/3394486"],"URL":"https:\/\/doi.org\/10.1145\/3394486.3403137","relation":{},"subject":[],"published":{"date-parts":[[2020,8,20]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}