{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T08:31:01Z","timestamp":1765960261398,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":35,"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":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61836005, 62272315, 62172283"],"award-info":[{"award-number":["61836005, 62272315, 62172283"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,4,30]]},"DOI":"10.1145\/3543507.3583382","type":"proceedings-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T23:30:51Z","timestamp":1682551851000},"page":"1673-1682","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["DIWIFT: Discovering Instance-wise Influential Features for Tabular Data"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3612-709X","authenticated-orcid":false,"given":"Dugang","family":"Liu","sequence":"first","affiliation":[{"name":"Shenzhen University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5997-705X","authenticated-orcid":false,"given":"Pengxiang","family":"Cheng","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co Ltd, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2943-7997","authenticated-orcid":false,"given":"Hong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co Ltd, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4360-0754","authenticated-orcid":false,"given":"Xing","family":"Tang","sequence":"additional","affiliation":[{"name":"FIT, Tencent, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1514-1116","authenticated-orcid":false,"given":"Yanyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Tsinghua-Berkeley Shenzhen Institute, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2135-8389","authenticated-orcid":false,"given":"Xiaoting","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua-Berkeley Shenzhen Institute, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6326-9531","authenticated-orcid":false,"given":"Weike","family":"Pan","sequence":"additional","affiliation":[{"name":"Shenzhen University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9310-3460","authenticated-orcid":false,"given":"Zhong","family":"Ming","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4115-8205","authenticated-orcid":false,"given":"Xiuqiang","family":"He","sequence":"additional","affiliation":[{"name":"Fit, Tencent, China"}]}],"member":"320","published-online":{"date-parts":[[2023,4,30]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16826"},{"key":"e_1_3_2_1_2_1","volume-title":"Deep neural networks and tabular data: A survey. arXiv preprint arXiv:2110.01889","author":"Borisov Vadim","year":"2021","unstructured":"Vadim Borisov, Tobias Leemann, Kathrin Se\u00dfler, Johannes Haug, Martin Pawelczyk, and Gjergji Kasneci. 2021. Deep neural networks and tabular data: A survey. arXiv preprint arXiv:2110.01889 (2021)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20309"},{"key":"e_1_3_2_1_4_1","volume-title":"Proceedings of the 35th International Conference on Machine Learning. 883\u2013892","author":"Chen Jianbo","year":"2018","unstructured":"Jianbo Chen, Le Song, Martin Wainwright, and Michael Jordan. 2018. Learning to explain: An information-theoretic perspective on model interpretation. In Proceedings of the 35th International Conference on Machine Learning. 883\u2013892."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.02.026"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3186963"},{"key":"e_1_3_2_1_7_1","first-page":"1","article-title":"Feature selection using lasso","volume":"30","author":"Fonti Valeria","year":"2017","unstructured":"Valeria Fonti and Eduard Belitser. 2017. Feature selection using lasso. VU Amsterdam Research Paper in Business Analytics 30 (2017), 1\u201325.","journal-title":"VU Amsterdam Research Paper in Business Analytics"},{"key":"e_1_3_2_1_8_1","volume-title":"Extremely randomized trees. Machine learning 63, 1","author":"Geurts Pierre","year":"2006","unstructured":"Pierre Geurts, Damien Ernst, and Louis Wehenkel. 2006. Extremely randomized trees. Machine learning 63, 1 (2006), 3\u201342."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944968"},{"volume-title":"International Encyclopedia of Statistical Science","author":"Huber J","key":"e_1_3_2_1_10_1","unstructured":"Peter\u00a0J Huber. 2011. Robust statistics. In International Encyclopedia of Statistical Science. Springer, 1248\u20131251."},{"key":"e_1_3_2_1_11_1","volume-title":"Proceedings of the 9th International Conference on Learning Representations.","author":"Katzir Liran","year":"2020","unstructured":"Liran Katzir, Gal Elidan, and Ran El-Yaniv. 2020. Net-DNF: Effective deep modeling of tabular data. In Proceedings of the 9th International Conference on Learning Representations."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449999"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning. 1885\u20131894","author":"Koh Pang\u00a0Wei","year":"2017","unstructured":"Pang\u00a0Wei Koh and Percy Liang. 2017. Understanding black-box predictions via influence functions. In Proceedings of the 34th International Conference on Machine Learning. 1885\u20131894."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. 202\u2013207","author":"Kohavi Ron","year":"1996","unstructured":"Ron Kohavi 1996. Scaling up the accuracy of naive-Bayes classifiers: A decision-tree hybrid. In Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. 202\u2013207."},{"key":"e_1_3_2_1_15_1","volume-title":"DNN2LR: Interpretation-inspired feature crossing for real-world tabular data. arXiv preprint arXiv:2008.09775","author":"Liu Zhaocheng","year":"2020","unstructured":"Zhaocheng Liu, Qiang Liu, Haoli Zhang, and Yuntian Chen. 2020. DNN2LR: Interpretation-inspired feature crossing for real-world tabular data. arXiv preprint arXiv:2008.09775 (2020)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330679"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401437"},{"key":"e_1_3_2_1_18_1","volume-title":"Optimizing feature set for click-through rate prediction. arXiv preprint arXiv:2301.10909","author":"Lyu Fuyuan","year":"2023","unstructured":"Fuyuan Lyu, Xing Tang, Dugang Liu, Liang Chen, Xiuqiang He, and Xue Liu. 2023. Optimizing feature set for click-through rate prediction. arXiv preprint arXiv:2301.10909 (2023)."},{"key":"e_1_3_2_1_19_1","volume-title":"Feature representation learning for click-through rate prediction: A review and new perspectives. arXiv preprint arXiv:2302.02241","author":"Lyu Fuyuan","year":"2023","unstructured":"Fuyuan Lyu, Xing Tang, Dugang Liu, Haolun Wu, Chen Ma, Xiuqiang He, and Xue Liu. 2023. Feature representation learning for click-through rate prediction: A review and new perspectives. arXiv preprint arXiv:2302.02241 (2023)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00194"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401440"},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the 35th International Conference on Machine Learning. 4334\u20134343","author":"Ren Mengye","year":"2018","unstructured":"Mengye Ren, Wenyuan Zeng, Bin Yang, and Raquel Urtasun. 2018. Learning to reweight examples for robust deep learning. In Proceedings of the 35th International Conference on Machine Learning. 4334\u20134343."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the 33rd International Conference on Machine Learning. 1670\u20131679","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 Proceedings of the 33rd International Conference on Machine Learning. 1670\u20131679."},{"key":"e_1_3_2_1_25_1","volume-title":"Proceedings of the 24th European Conference on Artificial Intelligence. 1491\u20131498","author":"\u0160krlj Bla\u017e","year":"2020","unstructured":"Bla\u017e \u0160krlj, Sa\u0161o D\u017eeroski, Nada Lavra\u010d, and Matej Petkovi\u010d. 2020. Feature importance estimation with self-attention networks. In Proceedings of the 24th European Conference on Artificial Intelligence. 1491\u20131498."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301718"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of the 35th Conference on Neural Information Processing Systems. 18853\u201318865","author":"Ucar Talip","year":"2021","unstructured":"Talip Ucar, Ehsan Hajiramezanali, and Lindsay Edwards. 2021. SubTab: Subsetting features of tabular data for self-supervised representation learning. In Proceedings of the 35th Conference on Neural Information Processing Systems. 18853\u201318865."},{"key":"e_1_3_2_1_28_1","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems. 6000\u20136010","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Proceedings of the 31st International Conference on Neural Information Processing Systems. 6000\u20136010."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2018.00017"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6103"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467066"},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the 6th International Conference on Learning Representations.","author":"Yoon Jinsung","year":"2018","unstructured":"Jinsung Yoon, James Jordon, and Mihaela van\u00a0der Schaar. 2018. INVASE: Instance-wise variable selection using neural networks. In Proceedings of the 6th International Conference on Learning Representations."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401321"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3158369"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"}],"event":{"name":"WWW '23: The ACM Web Conference 2023","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Austin TX USA","acronym":"WWW '23"},"container-title":["Proceedings of the ACM Web Conference 2023"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583382","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3543507.3583382","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:47:51Z","timestamp":1750178871000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583382"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,30]]},"references-count":35,"alternative-id":["10.1145\/3543507.3583382","10.1145\/3543507"],"URL":"https:\/\/doi.org\/10.1145\/3543507.3583382","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"}}]}}