{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T03:37:30Z","timestamp":1771299450379,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":39,"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":"National Key R&D Program of China","award":["2020YFB1707903"],"award-info":[{"award-number":["2020YFB1707903"]}]},{"name":"National Natural Science Foundation of China","award":["61972254"],"award-info":[{"award-number":["61972254"]}]},{"name":"National Natural Science Foundation of China","award":["61872238"],"award-info":[{"award-number":["61872238"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,7,11]]},"DOI":"10.1145\/3404835.3462831","type":"proceedings-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T02:41:52Z","timestamp":1626057712000},"page":"1177-1186","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["FORM: Follow the Online Regularized Meta-Leader for Cold-Start Recommendation"],"prefix":"10.1145","author":[{"given":"Xuehan","family":"Sun","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyao","family":"Shi","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Gao","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanrong","family":"Kang","sequence":"additional","affiliation":[{"name":"Tencent Advertising and Marketing Service, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guihai","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,11]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Preprints Conf. Optimality in Artificial and Biological Neural Networks","volume":"2","author":"Bengio Samy","year":"1992","unstructured":"Samy Bengio, Yoshua Bengio, Jocelyn Cloutier, and Jan Gecsei. 1992. On the optimization of a synaptic learning rule. In Preprints Conf. Optimality in Artificial and Biological Neural Networks, Vol. 2. Univ. of Texas."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Heng-Tze Cheng Levent Koc Jeremiah Harmsen Tal Shaked Tushar Chandra Hrishi Aradhye Glen Anderson Greg Corrado Wei Chai Mustafa Ispir Rohan Anil Zakaria Haque Lichan Hong Vihan Jain Xiaobing Liu and Hemal Shah. 2016. Wide & Deep Learning for Recommender Systems (DLRS 2016). ACM 7--10.","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330726"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313488"},{"key":"e_1_3_2_1_5_1","volume-title":"Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. In International Conference on Machine Learning (ICML). 1126--1135","author":"Finn Chelsea","year":"2017","unstructured":"Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. In International Conference on Machine Learning (ICML). 1126--1135."},{"key":"e_1_3_2_1_6_1","volume-title":"International Conference on Machine Learning (ICML). 1920--1930","author":"Finn Chelsea","year":"2019","unstructured":"Chelsea Finn, Aravind Rajeswaran, Sham Kakade, and Sergey Levine. 2019. Online meta-learning. In International Conference on Machine Learning (ICML). 1920--1930."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/239"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403357"},{"key":"e_1_3_2_1_9_1","volume-title":"Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval.","author":"Hansen Casper","unstructured":"Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Stephen Alstrup, and Christina Lioma. [n. d.]. Content-aware Neural Hashing for Cold-start Recommendation. In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2827872"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcss.2004.10.016"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330859"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014189"},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the 19th International Conference on World Wide Web (WWW '10)","author":"Li Lihong","unstructured":"Lihong Li, Wei Chu, John Langford, and Robert E. Schapire. 2010a. A contextual-bandit approach to personalized news article recommendation. In Proceedings of the 19th International Conference on World Wide Web (WWW '10). ACM, 661--670."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772758"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403314"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11245"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403207"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488200"},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the 27th International Conference on International Conference on Machine Learning (ICML'10)","author":"Nair Vinod","unstructured":"Vinod Nair and Geoffrey E. Hinton. 2010. Rectified Linear Units Improve Restricted Boltzmann Machines. In Proceedings of the 27th International Conference on International Conference on Machine Learning (ICML'10). Omnipress, 807--814."},{"key":"e_1_3_2_1_24_1","volume-title":"J\u00e9 r\u00e9 mie Mary, and Philippe Preux","author":"Nguyen Hai Thanh","year":"2014","unstructured":"Hai Thanh Nguyen, J\u00e9 r\u00e9 mie Mary, and Philippe Preux. 2014. Cold-start Problems in Recommendation Systems via Contextual-bandit Algorithms. CoRR, Vol. abs\/1405.7544 (2014)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331268"},{"key":"e_1_3_2_1_26_1","volume-title":"Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI '09)","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI '09). 452--461."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098041"},{"key":"e_1_3_2_1_29_1","unstructured":"Manasi Vartak Arvind Thiagarajan Conrado Miranda Jeshua Bratman and Hugo Larochelle. 2017. A meta-learning perspective on cold-start recommendations for items. In Advances in Neural Information Processing Systems. 6904--6914."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1019956318069"},{"key":"e_1_3_2_1_31_1","volume-title":"Guang Wei Yu, and Tomi Poutanen","author":"Volkovs Maksims","year":"2017","unstructured":"Maksims Volkovs, Guang Wei Yu, and Tomi Poutanen. 2017. DropoutNet: Addressing Cold Start in Recommender Systems. In Advances in Neural Information Processing Systems. 4957--4966."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313411"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_34_1","volume-title":"Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning. In 2020 IEEE International Conference on Data Mining.","author":"Wei Tianxin","year":"2020","unstructured":"Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, and Wei Wang. 2020. Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning. In 2020 IEEE International Conference on Data Mining."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412752"},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 1479--1488","author":"Zhang Yang","year":"2020","unstructured":"Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li, and Yongdong Zhang. 2020. How to retrain recommender system? A sequential meta-learning method. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 1479--1488."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505690"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3185994"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16601"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"}],"event":{"name":"SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Virtual Event Canada","acronym":"SIGIR '21","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"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\/3404835.3462831","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404835.3462831","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:16Z","timestamp":1750193236000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462831"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,11]]},"references-count":39,"alternative-id":["10.1145\/3404835.3462831","10.1145\/3404835"],"URL":"https:\/\/doi.org\/10.1145\/3404835.3462831","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"}}]}}