{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T03:04:44Z","timestamp":1773543884807,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,4,30]],"date-time":"2023-04-30T00:00:00Z","timestamp":1682812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study","award":["SN-ZJU-SIAS-001"],"award-info":[{"award-number":["SN-ZJU-SIAS-001"]}]},{"name":"the National Natural Science Foundation of China","award":["61972372, 62121002, 62102382"],"award-info":[{"award-number":["61972372, 62121002, 62102382"]}]},{"name":"the CCCD Key Lab of Ministry of Culture and Tourism"},{"name":"the National Key Research and Development Program of China","award":["2022YFB3104701"],"award-info":[{"award-number":["2022YFB3104701"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,4,30]]},"DOI":"10.1145\/3543507.3583223","type":"proceedings-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T23:30:51Z","timestamp":1682551851000},"page":"812-822","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":29,"title":["On the Theories Behind Hard Negative Sampling for Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2616-6880","authenticated-orcid":false,"given":"Wentao","family":"Shi","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4752-2629","authenticated-orcid":false,"given":"Jiawei","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5828-9842","authenticated-orcid":false,"given":"Fuli","family":"Feng","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0251-465X","authenticated-orcid":false,"given":"Jizhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6663-926X","authenticated-orcid":false,"given":"Junkang","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5187-9196","authenticated-orcid":false,"given":"Chongming","family":"Gao","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8472-7992","authenticated-orcid":false,"given":"Xiangnan","family":"He","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, China"}]}],"member":"320","published-online":{"date-parts":[[2023,4,30]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Immanuel Bayer Xiangnan He Bhargav Kanagal and Steffen Rendle. 2017. A Generic Coordinate Descent Framework for Learning from Implicit Feedback. In WWW. ACM 1341\u20131350.","DOI":"10.1145\/3038912.3052694"},{"key":"e_1_3_2_1_2_1","unstructured":"Guy Blanc and Steffen Rendle. 2018. Adaptive Sampled Softmax with Kernel Based Sampling. In ICML. 590\u2013599."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Hugo Caselles-Dupr\u00e9 Florian Lesaint and Jimena Royo-Letelier. 2018. Word2vec applied to recommendation: hyperparameters matter. In RecSys. 352\u2013356.","DOI":"10.1145\/3240323.3240377"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Chong Chen Weizhi Ma Min Zhang Chenyang Wang Yiqun Liu and Shaoping Ma. 2022. Revisiting Negative Sampling VS. Non-Sampling in Implicit Recommendation. ACM Trans. Inf. Syst. (2022).","DOI":"10.1145\/3522672"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Chong Chen Min Zhang Weizhi Ma Yongfeng Zhang Yiqun Liu and Shaoping Ma. 2020. Ef\ufb01cient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation. In AAAI.","DOI":"10.1609\/aaai.v34i01.5329"},{"key":"e_1_3_2_1_6_1","volume-title":"Efficient Neural Matrix Factorization without Sampling for Recommendation. ACM Trans. Inf. Syst. 38","author":"Chen Chong","year":"2020","unstructured":"Chong Chen, Min Zhang, Yongfeng Zhang, Yiqun Liu, and Shaoping Ma. 2020. Efficient Neural Matrix Factorization without Sampling for Recommendation. ACM Trans. Inf. Syst. 38 (2020)."},{"key":"e_1_3_2_1_7_1","volume-title":"Bias and Debias in Recommender System: A Survey and Future Directions. CoRR abs\/2010.03240","author":"Chen Jiawei","year":"2020","unstructured":"Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, and Xiangnan He. 2020. Bias and Debias in Recommender System: A Survey and Future Directions. CoRR abs\/2010.03240 (2020)."},{"key":"e_1_3_2_1_8_1","volume-title":"CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation. ACM Trans. Inf. Syst. 39","author":"Chen Jiawei","year":"2021","unstructured":"Jiawei Chen, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester, and Xiangnan He. 2021. CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation. ACM Trans. Inf. Syst. 39 (2021)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Jin Chen Defu Lian Binbin Jin Kai Zheng and Enhong Chen. 2022. Learning Recommenders for Implicit Feedback with Importance Resampling. In WWW. 1997\u20132005.","DOI":"10.1145\/3485447.3512075"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Ting Chen Yizhou Sun Yue Shi and Liangjie Hong. 2017. On Sampling Strategies for Neural Network-based Collaborative Filtering. In SIGKDD.","DOI":"10.1145\/3097983.3098202"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Jingtao Ding Yuhan Quan Xiangnan He Yong Li and Depeng Jin. 2019. Reinforced Negative Sampling for Recommendation with Exposure Data. In IJCAI. 2230\u20132236.","DOI":"10.24963\/ijcai.2019\/309"},{"key":"e_1_3_2_1_12_1","unstructured":"Jingtao Ding Yuhan Quan Quanming Yao Yong Li and Depeng Jin. 2020. Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering. In NIPS. 1094\u20131105."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1111\/1541-0420.00071"},{"key":"e_1_3_2_1_14_1","volume-title":"Duchi and Hongseok Namkoong","author":"C.","year":"2018","unstructured":"John\u00a0C. Duchi and Hongseok Namkoong. 2018. Learning Models with Uniform Performance via Distributionally Robust Optimization. CoRR abs\/1810.08750 (2018)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Louis Faury Ugo Tanielian Elvis Dohmatob Elena Smirnova and Flavian Vasile. 2020. Distributionally Robust Counterfactual Risk Minimization. In AAAI. 3850\u20133857.","DOI":"10.1609\/aaai.v34i04.5797"},{"key":"e_1_3_2_1_16_1","unstructured":"Wei Gao and Zhi-Hua Zhou. 2015. On the Consistency of AUC Pairwise Optimization. In IJCAI. 939\u2013945."},{"key":"e_1_3_2_1_17_1","unstructured":"Xiangnan He Hanwang Zhang Min-Yen Kan and Tat-Seng Chua. 2016. Fast Matrix Factorization for Online Recommendation with Implicit Feedback. In SIGIR. ACM 549\u2013558."},{"key":"e_1_3_2_1_18_1","volume-title":"Kullback-Leibler divergence constrained distributionally robust optimization. Available at Optimization Online","author":"Hu Zhaolin","year":"2013","unstructured":"Zhaolin Hu and L\u00a0Jeff Hong. 2013. Kullback-Leibler divergence constrained distributionally robust optimization. Available at Optimization Online (2013), 1695\u20131724."},{"key":"e_1_3_2_1_19_1","unstructured":"Daniel Levy Yair Carmon John\u00a0C Duchi and Aaron Sidford. 2020. Large-Scale Methods for Distributionally Robust Optimization. In NIPS Vol.\u00a033. 8847\u20138860."},{"key":"e_1_3_2_1_20_1","unstructured":"Nan Li Rong Jin and Zhi-Hua Zhou. 2014. Top Rank Optimization in Linear Time. In NIPS. 1502\u20131510."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Defu Lian Qi Liu and Enhong Chen. 2020. Personalized Ranking with Importance Sampling. In WWW. 1093\u20131103.","DOI":"10.1145\/3366423.3380187"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.3934\/naco.2021057"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Xin Mao Wenting Wang Yuanbin Wu and Man Lan. 2021. Boosting the Speed of Entity Alignment 10 \u00d7: Dual Attention Matching Network with Normalized Hard Sample Mining. In WWW. 821\u2013832.","DOI":"10.1145\/3442381.3449897"},{"key":"e_1_3_2_1_24_1","volume-title":"Analyzing a portion of the ROC Curve. Medical decision making : an international journal of the Society for Medical Decision Making 9","author":"McClish Donna","year":"1989","unstructured":"Donna McClish. 1989. Analyzing a portion of the ROC Curve. Medical decision making : an international journal of the Society for Medical Decision Making 9 (1989), 190\u20135."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2021.582928"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Dae\u00a0Hoon Park and Yi Chang. 2019. Adversarial Sampling and Training for Semi-Supervised Information Retrieval. In WWW. 1443\u20131453.","DOI":"10.1145\/3308558.3313416"},{"key":"e_1_3_2_1_27_1","volume-title":"Distributionally Robust Optimization: A Review. CoRR abs\/1908.05659","author":"Rahimian Hamed","year":"2019","unstructured":"Hamed Rahimian and Sanjay Mehrotra. 2019. Distributionally Robust Optimization: A Review. CoRR abs\/1908.05659 (2019)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Steffen Rendle and Christoph Freudenthaler. 2014. Improving Pairwise Learning for Item Recommendation from Implicit Feedback. In WSDM. 273\u2013282.","DOI":"10.1145\/2556195.2556248"},{"key":"e_1_3_2_1_29_1","volume-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI. 452\u2013461.","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 UAI. 452\u2013461."},{"key":"e_1_3_2_1_30_1","volume-title":"Jonathan M. Borwein Commemorative Conference. 21\u201342","author":"Rockafellar R\u00a0Tyrrell","year":"2017","unstructured":"R\u00a0Tyrrell Rockafellar. 2017. Risk and utility in the duality framework of convex analysis. In Jonathan M. Borwein Commemorative Conference. 21\u201342."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.5555\/1577069.1755861"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Qi Wan Xiangnan He Xiang Wang Jiancan Wu Wei Guo and Ruiming Tang. 2022. Cross Pairwise Ranking for Unbiased Item Recommendation. In WWW. 2370\u20132378.","DOI":"10.1145\/3485447.3512010"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080786"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Yaokun Xu Xiangnan He Yixin Cao Meng Wang and Tat-Seng Chua. 2020. Reinforced Negative Sampling over Knowledge Graph for Recommendation. In WWW. 99\u2013109.","DOI":"10.1145\/3366423.3380098"},{"key":"e_1_3_2_1_35_1","volume-title":"WSABIE: Scaling up to Large Vocabulary Image Annotation. In IJCAI. 2764\u20132770.","author":"Weston Jason","year":"2011","unstructured":"Jason Weston, Samy Bengio, and Nicolas Usunier. 2011. WSABIE: Scaling up to Large Vocabulary Image Annotation. In IJCAI. 2764\u20132770."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Shan-Hung Wu Keng-Pei Lin Chung-Min Chen and Ming-Syan Chen. 2008. Asymmetric support vector machines: low false-positive learning under the user tolerance. In KDD. ACM 749\u2013757.","DOI":"10.1145\/1401890.1401980"},{"key":"e_1_3_2_1_37_1","volume-title":"AUC Maximization in the Era of Big Data and AI: A Survey. ACM Comput. Surv. (jul","author":"Yang Tianbao","year":"2022","unstructured":"Tianbao Yang and Yiming Ying. 2022. AUC Maximization in the Era of Big Data and AI: A Survey. ACM Comput. Surv. (jul 2022)."},{"key":"e_1_3_2_1_38_1","unstructured":"Zhiyong Yang Qianqian Xu Shilong Bao Yuan He Xiaochun Cao and Qingming Huang. 2021. When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC. In ICML. 11820\u201311829."},{"key":"e_1_3_2_1_39_1","volume-title":"DORO: Distributional and Outlier Robust Optimization. In ICML. 12345\u201312355.","author":"Zhai Runtian","year":"2021","unstructured":"Runtian Zhai, Chen Dan, J.\u00a0Zico Kolter, and Pradeep Ravikumar. 2021. DORO: Distributional and Outlier Robust Optimization. In ICML. 12345\u201312355."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Tianqi Chen Jun Wang and Yong Yu. 2013. Optimizing top-n collaborative filtering via dynamic negative item sampling. In SIGIR. 785\u2013788.","DOI":"10.1145\/2484028.2484126"},{"key":"e_1_3_2_1_41_1","unstructured":"Dixian Zhu Gang Li Bokun Wang Xiaodong Wu and Tianbao Yang. 2022. When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee. In ICML. 27548\u201327573."},{"key":"e_1_3_2_1_42_1","unstructured":"Qiannan Zhu Haobo Zhang Qing He and Zhicheng Dou. 2022. A Gain-Tuning Dynamic Negative Sampler for Recommendation. In WWW. 277\u2013285."}],"event":{"name":"WWW '23: The ACM Web Conference 2023","location":"Austin TX USA","acronym":"WWW '23","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2023"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583223","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3543507.3583223","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:18Z","timestamp":1750183758000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583223"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,30]]},"references-count":42,"alternative-id":["10.1145\/3543507.3583223","10.1145\/3543507"],"URL":"https:\/\/doi.org\/10.1145\/3543507.3583223","relation":{},"subject":[],"published":{"date-parts":[[2023,4,30]]},"assertion":[{"value":"2023-04-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}