{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T10:00:51Z","timestamp":1775815251470,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3539439","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:12Z","timestamp":1660331172000},"page":"1969-1978","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":57,"title":["Invariant Preference Learning for General Debiasing in Recommendation"],"prefix":"10.1145","author":[{"given":"Zimu","family":"Wang","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Yue","family":"He","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Jiashuo","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Wenchao","family":"Zou","sequence":"additional","affiliation":[{"name":"Siemens China, Shanghai, China"}]},{"given":"Philip S.","family":"Yu","sequence":"additional","affiliation":[{"name":"University of Illinois at Chicago, Chicago, IL, USA"}]},{"given":"Peng","family":"Cui","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109912"},{"key":"e_1_3_2_2_2_1","volume-title":"Invariance principle meets information bottleneck for out-of-distribution generalization. Advances in Neural Information Processing Systems 34","author":"Ahuja Kartik","year":"2021","unstructured":"Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, and Irina Rish. 2021. Invariance principle meets information bottleneck for out-of-distribution generalization. Advances in Neural Information Processing Systems 34 (2021)."},{"key":"e_1_3_2_2_3_1","first-page":"304","article-title":"Handwriting Arabic character recognition LeNet using neural network","volume":"6","author":"Al-Jawfi Rashad","year":"2009","unstructured":"Rashad Al-Jawfi. 2009. Handwriting Arabic character recognition LeNet using neural network. Int. Arab J. Inf. Technol. 6, 3 (2009), 304--309.","journal-title":"Int. Arab J. Inf. Technol."},{"key":"e_1_3_2_2_4_1","volume-title":"Invariant risk minimization. arXiv preprint arXiv:1907.02893","author":"Arjovsky Martin","year":"2019","unstructured":"Martin Arjovsky, L\u00e9on Bottou, Ishaan Gulrajani, and David Lopez-Paz. 2019. Invariant risk minimization. arXiv preprint arXiv:1907.02893 (2019)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240360"},{"key":"e_1_3_2_2_6_1","first-page":"404","article-title":"Invariance, causality and robustness","volume":"35","author":"B\u00fchlmann Peter","year":"2020","unstructured":"Peter B\u00fchlmann. 2020. Invariance, causality and robustness. Statist. Sci. 35, 3 (2020), 404--426.","journal-title":"Statist. Sci."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462919"},{"key":"e_1_3_2_2_8_1","volume-title":"International conference on machine learning. PMLR, 1180--1189","author":"Ganin Yaroslav","year":"2015","unstructured":"Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised domain adaptation by backpropagation. In International conference on machine learning. PMLR, 1180--1189."},{"key":"e_1_3_2_2_9_1","volume-title":"Domain-adversarial training of neural networks. The journal of machine learning research 17, 1","author":"Ganin Yaroslav","year":"2016","unstructured":"Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, Fran\u00e7ois Laviolette, Mario Marchand, and Victor Lempitsky. 2016. Domain-adversarial training of neural networks. The journal of machine learning research 17, 1 (2016), 2096--2030."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","unstructured":"Yue He Zimu Wang Peng Cui Hao Zou Yafeng Zhang Qiang Cui and Yong Jiang. 2022. CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. (2022). https:\/\/doi.org\/10.1145\/3485447.3511969 arXiv:arXiv:2202.03984","DOI":"10.1145\/3485447.3511969"},{"key":"e_1_3_2_2_11_1","volume-title":"International Conference on Machine Learning. PMLR, 1512--1520","author":"Hern\u00e1ndez-Lobato Jos\u00e9 Miguel","year":"2014","unstructured":"Jos\u00e9 Miguel Hern\u00e1ndez-Lobato, Neil Houlsby, and Zoubin Ghahramani. 2014. Probabilistic matrix factorization with non-random missing data. In International Conference on Machine Learning. PMLR, 1512--1520."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412252"},{"key":"e_1_3_2_2_14_1","volume-title":"International Conference on Machine Learning. PMLR, 652--661","author":"Jiang Nan","year":"2016","unstructured":"Nan Jiang and Lihong Li. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In International Conference on Machine Learning. PMLR, 652--661."},{"key":"e_1_3_2_2_15_1","volume-title":"On Invariance Penalties for Risk Minimization. arXiv preprint arXiv:2106.09777","author":"Khezeli Kia","year":"2021","unstructured":"Kia Khezeli, Arno Blaas, Frank Soboczenski, Nicholas Chia, and John Kalantari. 2021. On Invariance Penalties for Risk Minimization. arXiv preprint arXiv:2106.09777 (2021)."},{"key":"e_1_3_2_2_16_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_18_1","unstructured":"Masanori Koyama and Shoichiro Yamaguchi. 2021. When is invariance useful in an Out-of-Distribution Generalization problem? arXiv:2008.01883 [stat.ML]"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00566"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883090"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401083"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474263"},{"key":"e_1_3_2_2_23_1","volume-title":"Shiori Sagawa, Percy Liang, and Chelsea Finn.","author":"Liu Evan Zheran","year":"2021","unstructured":"Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, and Chelsea Finn. 2021. Just Train Twice: Improving Group Robustness without Training Group Information. arXiv:2107.09044 [cs.LG]"},{"key":"e_1_3_2_2_24_1","volume-title":"International Conference on Machine Learning. PMLR, 6804--6814","author":"Liu Jiashuo","year":"2021","unstructured":"Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, and Zheyan Shen. 2021. Heterogeneous risk minimization. In International Conference on Machine Learning. PMLR, 6804--6814."},{"key":"e_1_3_2_2_25_1","volume-title":"Collaborative filtering and the missing at random assumption. arXiv preprint arXiv:1206.5267","author":"Marlin Benjamin","year":"2012","unstructured":"Benjamin Marlin, Richard S Zemel, Sam Roweis, and Malcolm Slaney. 2012. Collaborative filtering and the missing at random assumption. arXiv preprint arXiv:1206.5267 (2012)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401114"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371783"},{"key":"e_1_3_2_2_28_1","volume-title":"international conference on machine learning. PMLR, 1670--1679","author":"Schnabel Tobias","year":"2016","unstructured":"Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, and Thorsten Joachims. 2016. Recommendations as treatments: Debiasing learning and evaluation. In international conference on machine learning. PMLR, 1670--1679."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240577"},{"key":"e_1_3_2_2_30_1","volume-title":"The self-normalized estimator for counterfactual learning. advances in neural information processing systems 28","author":"Swaminathan Adith","year":"2015","unstructured":"Adith Swaminathan and Thorsten Joachims. 2015. The self-normalized estimator for counterfactual learning. advances in neural information processing systems 28 (2015)."},{"key":"e_1_3_2_2_31_1","volume-title":"The information bottleneck method. arXiv preprint physics\/0004057","author":"Tishby Naftali","year":"2000","unstructured":"Naftali Tishby, Fernando C Pereira, and William Bialek. 2000. The information bottleneck method. arXiv preprint physics\/0004057 (2000)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462962"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052556"},{"key":"e_1_3_2_2_35_1","volume-title":"International Conference on Machine Learning. PMLR, 6638--6647","author":"Wang Xiaojie","year":"2019","unstructured":"Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi. 2019. Doubly robust joint learning for recommendation on data missing not at random. In International Conference on Machine Learning. PMLR, 6638--6647."},{"key":"e_1_3_2_2_36_1","first-page":"1854","article-title":"Information theoretic counterfactual learning from missing-not-at- random feedback","volume":"33","author":"Wang Zifeng","year":"2020","unstructured":"Zifeng Wang, Xi Chen, Rui Wen, Shao-Lun Huang, Ercan Kuruoglu, and Yefeng Zheng. 2020. Information theoretic counterfactual learning from missing-not-at- random feedback. Advances in Neural Information Processing Systems 33 (2020), 1854--1864.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467289"},{"key":"e_1_3_2_2_38_1","volume-title":"A survey on neural recommendation: From collaborative filtering to content and context enriched recommendation. arXiv preprint arXiv:2104.13030","author":"Wu Le","year":"2021","unstructured":"Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, and Meng Wang. 2021. A survey on neural recommendation: From collaborative filtering to content and context enriched recommendation. arXiv preprint arXiv:2104.13030 (2021)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240355"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449788"}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Washington DC USA","acronym":"KDD '22","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 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539439","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539439","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:03:03Z","timestamp":1750186983000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539439"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":40,"alternative-id":["10.1145\/3534678.3539439","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539439","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}