{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T19:45:50Z","timestamp":1759693550925,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,11]],"date-time":"2021-07-11T00:00:00Z","timestamp":1625961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSFC","award":["61936011"],"award-info":[{"award-number":["61936011"]}]},{"name":"Beijing Key Lab of Networked Multimedia"},{"DOI":"10.13039\/100000002","name":"NIH (National Institutes of Health)","doi-asserted-by":"publisher","award":["R01LM013151"],"award-info":[{"award-number":["R01LM013151"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,7,11]]},"DOI":"10.1145\/3404835.3462842","type":"proceedings-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T02:41:54Z","timestamp":1626057714000},"page":"1298-1307","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["A General Method For Automatic Discovery of Powerful Interactions In Click-Through Rate Prediction"],"prefix":"10.1145","author":[{"given":"Ze","family":"Meng","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Jinnian","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Wisconsin Madison, Madison, WI, USA"}]},{"given":"Yumeng","family":"Li","sequence":"additional","affiliation":[{"name":"Alibaba Group, Beijing, China"}]},{"given":"Jiancheng","family":"Li","sequence":"additional","affiliation":[{"name":"Alibaba Group, Beijing, China"}]},{"given":"Tanchao","family":"Zhu","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Lifeng","family":"Sun","sequence":"additional","affiliation":[{"name":"Ministry of Education & Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2021,7,11]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Higher-order factorization machines. arXiv preprint arXiv:1607.07195","author":"Blondel Mathieu","year":"2016","unstructured":"Mathieu Blondel, Akinori Fujino, Naonori Ueda, and Masakazu Ishihata. 2016. Higher-order factorization machines. arXiv preprint arXiv:1607.07195 (2016)."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5768"},{"key":"e_1_3_2_2_4_1","volume-title":"Noisy differentiable architecture search. arXiv preprint arXiv:2005.03566","author":"Chu Xiangxiang","year":"2020","unstructured":"Xiangxiang Chu, Bo Zhang, and Xudong Li. 2020. Noisy differentiable architecture search. arXiv preprint arXiv:2005.03566 (2020)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_28"},{"key":"e_1_3_2_2_6_1","first-page":"1","article-title":"Neural architecture search: A survey","volume":"20","author":"Elsken Thomas","year":"2019","unstructured":"Thomas Elsken, Jan Hendrik Metzen, Frank Hutter, et al. 2019. Neural architecture search: A survey. J. Mach. Learn. Res. 20, 55 (2019), 1--21.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_2_7_1","unstructured":"Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: a factorization-machine based neural network for CTR prediction. arXiv preprint arXiv:1703.04247 (2017)."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080777"},{"key":"e_1_3_2_2_9_1","volume-title":"Multilayer feedforward networks are universal approximators. Neural networks 2, 5","author":"Hornik Kurt","year":"1989","unstructured":"Kurt Hornik, Maxwell Stinchcombe, and Halbert White. 1989. Multilayer feedforward networks are universal approximators. Neural networks 2, 5 (1989), 359--366."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347043"},{"key":"e_1_3_2_2_11_1","volume-title":"International conference on machine learning. PMLR, 448--456","author":"Ioffe Sergey","year":"2015","unstructured":"Sergey Ioffe and Christian Szegedy. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. In International conference on machine learning. PMLR, 448--456."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411912"},{"key":"e_1_3_2_2_13_1","volume-title":"PD-DARTS: Progressive Discretization Differentiable Architecture Search. In International Conference on Pattern Recognition and Artificial Intelligence. Springer, 306--311","author":"Li Yonggang","year":"2020","unstructured":"Yonggang Li, Yafeng Zhou, Yongtao Wang, and Zhi Tang. 2020. PD-DARTS: Progressive Discretization Differentiable Architecture Search. In International Conference on Pattern Recognition and Artificial Intelligence. Springer, 306--311."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_2_15_1","volume-title":"Improved differentiable architecture search with early stopping. arXiv preprint arXiv:1909.06035","author":"Liang Hanwen","year":"2019","unstructured":"Hanwen Liang, Shifeng Zhang, Jiacheng Sun, Xingqiu He,Weiran Huang, Kechen Zhuang, and Zhenguo Li. 2019. Darts+: Improved differentiable architecture search with early stopping. arXiv preprint arXiv:1909.06035 (2019)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313497"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401082"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403314"},{"key":"e_1_3_2_2_19_1","volume-title":"Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055","author":"Liu Hanxiao","year":"2018","unstructured":"Hanxiao Liu, Karen Simonyan, and Yiming Yang. 2018. Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055 (2018)."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330679"},{"key":"e_1_3_2_2_21_1","volume-title":"International Conference on Machine Learning. PMLR, 4095--4104","author":"Pham Hieu","year":"2018","unstructured":"Hieu Pham, Melody Guan, Barret Zoph, Quoc Le, and Jeff Dean. 2018. Efficient neural architecture search via parameters sharing. In International Conference on Machine Learning. PMLR, 4095--4104."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3233770"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"e_1_3_2_2_24_1","volume-title":"A comprehensive survey of neural architecture search: Challenges and solutions. arXiv preprint arXiv:2006.02903","author":"Ren Pengzhen","year":"2020","unstructured":"Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, and Xin Wang. 2020. A comprehensive survey of neural architecture search: Challenges and solutions. arXiv preprint arXiv:2006.02903 (2020)."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168771"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403137"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357925"},{"key":"e_1_3_2_2_28_1","volume-title":"Proceedings of the ADKDD'17","author":"Fu Bin","year":"2017","unstructured":"RuoxiWang, Bin Fu, Gang Fu, and MingliangWang. 2017. Deep & cross network for ad click predictions. In Proceedings of the ADKDD'17. 1--7."},{"key":"e_1_3_2_2_29_1","volume-title":"AutoRec: An Automated Recommender System. In Fourteenth ACM Conference on Recommender Systems. 582--584","author":"Hu Xia","year":"2020","unstructured":"Ting-HsiangWang, Xia Hu, Haifeng Jin, Qingquan Song, Xiaotian Han, and Zirui Liu. 2020. AutoRec: An Automated Recommender System. In Fourteenth ACM Conference on Recommender Systems. 582--584."},{"key":"e_1_3_2_2_30_1","volume-title":"Attentional factorization machines: Learning the weight of feature interactions via attention networks. arXiv preprint arXiv:1708.04617","author":"Xiao Jun","year":"2017","unstructured":"Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua. 2017. Attentional factorization machines: Learning the weight of feature interactions via attention networks. arXiv preprint arXiv:1708.04617 (2017)."},{"key":"e_1_3_2_2_31_1","unstructured":"Lingxi Xie Xin Chen Kaifeng Bi Longhui Wei Yuhui Xu Zhengsu Chen Lanfei Wang An Xiao Jianlong Chang Xiaopeng Zhang et al. 2020. Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap. arXiv preprint arXiv:2008.01475 (2020)."},{"key":"e_1_3_2_2_32_1","volume-title":"Pc-darts: Partial channel connections for memory-efficient differentiable architecture search. arXiv preprint arXiv:1907.05737","author":"Xu Yuhui","year":"2019","unstructured":"Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, and Hongkai Xiong. 2019. Pc-darts: Partial channel connections for memory-efficient differentiable architecture search. arXiv preprint arXiv:1907.05737 (2019)."}],"event":{"name":"SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Virtual Event Canada","acronym":"SIGIR '21"},"container-title":["Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462842","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404835.3462842","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:17Z","timestamp":1750193237000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462842"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,11]]},"references-count":32,"alternative-id":["10.1145\/3404835.3462842","10.1145\/3404835"],"URL":"https:\/\/doi.org\/10.1145\/3404835.3462842","relation":{},"subject":[],"published":{"date-parts":[[2021,7,11]]},"assertion":[{"value":"2021-07-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}