{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T09:52:29Z","timestamp":1773481949829,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T00:00:00Z","timestamp":1691107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Guangzhou Science and Technology Plan Guangzhou-HKUST(GZ) Joint Project","award":["No. 2023A03J0144"],"award-info":[{"award-number":["No. 2023A03J0144"]}]},{"name":"Foshan HKUST Projects","award":["FSUST21-FYTRI01A FSUST21-FYTRI02A"],"award-info":[{"award-number":["FSUST21-FYTRI01A FSUST21-FYTRI02A"]}]},{"name":"National Natural Science Foundation of China","award":["No.62102110"],"award-info":[{"award-number":["No.62102110"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,8,6]]},"DOI":"10.1145\/3580305.3599842","type":"proceedings-article","created":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T18:13:58Z","timestamp":1691172838000},"page":"4100-4111","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1542-6149","authenticated-orcid":false,"given":"Jindong","family":"Han","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4271-1567","authenticated-orcid":false,"given":"Hao","family":"Liu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou) & Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3758-172X","authenticated-orcid":false,"given":"Shui","family":"Liu","sequence":"additional","affiliation":[{"name":"Didichuxing Co. Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2275-7039","authenticated-orcid":false,"given":"Xi","family":"Chen","sequence":"additional","affiliation":[{"name":"Didichuxing Co. Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4687-5212","authenticated-orcid":false,"given":"Naiqiang","family":"Tan","sequence":"additional","affiliation":[{"name":"Didichuxing Co. Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8351-1935","authenticated-orcid":false,"given":"Hua","family":"Chai","sequence":"additional","affiliation":[{"name":"Didichuxing Co. Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6016-6465","authenticated-orcid":false,"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou) & Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2023,8,4]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16)","author":"Abadi Mart'in","year":"2016","unstructured":"Mart'in Abadi , Paul Barham , Jianmin Chen , Zhifeng Chen , Andy Davis , Jeffrey Dean , Matthieu Devin , Sanjay Ghemawat , Geoffrey Irving , Michael Isard , 2016 . TensorFlow: a system for large-scale machine learning . In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16) . 265--283. Mart'in Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al. 2016. TensorFlow: a system for large-scale machine learning. In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16). 265--283."},{"key":"e_1_3_2_2_2_1","first-page":"388","article-title":"Incremental and decremental support vector machine learning","volume":"13","author":"Cauwenberghs Gert","year":"2000","unstructured":"Gert Cauwenberghs and Tomaso Poggio . 2000 . Incremental and decremental support vector machine learning . Advances in Neural Information Processing Systems , Vol. 13 (2000), 388 -- 394 . Gert Cauwenberghs and Tomaso Poggio. 2000. Incremental and decremental support vector machine learning. Advances in Neural Information Processing Systems , Vol. 13 (2000), 388--394.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/498"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539051"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_7_1","first-page":"3366","article-title":"A continual learning survey: Defying forgetting in classification tasks","volume":"44","author":"Lange Matthias De","year":"2021","unstructured":"Matthias De Lange , Rahaf Aljundi , Marc Masana , Sarah Parisot , Xu Jia , Alevs Leonardis , Gregory Slabaugh , and Tinne Tuytelaars . 2021 . A continual learning survey: Defying forgetting in classification tasks . IEEE Transactions on Pattern Analysis and Machine Intelligence , Vol. 44 , 7 (2021), 3366 -- 3385 . Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Alevs Leonardis, Gregory Slabaugh, and Tinne Tuytelaars. 2021. A continual learning survey: Defying forgetting in classification tasks. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 44, 7 (2021), 3366--3385.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481916"},{"key":"e_1_3_2_2_9_1","volume-title":"DEPTS: deep expansion learning for periodic time series forecasting. arXiv preprint arXiv:2203.07681","author":"Fan Wei","year":"2022","unstructured":"Wei Fan , Shun Zheng , Xiaohan Yi , Wei Cao , Yanjie Fu , Jiang Bian , and Tie-Yan Liu . 2022. DEPTS: deep expansion learning for periodic time series forecasting. arXiv preprint arXiv:2203.07681 ( 2022 ). Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, and Tie-Yan Liu. 2022. DEPTS: deep expansion learning for periodic time series forecasting. arXiv preprint arXiv:2203.07681 (2022)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403320"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403386"},{"key":"e_1_3_2_2_12_1","volume-title":"Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. JMLR Workshop and Conference Proceedings, 249--256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio . 2010 . Understanding the difficulty of training deep feedforward neural networks . In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. JMLR Workshop and Conference Proceedings, 249--256 . Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. JMLR Workshop and Conference Proceedings, 249--256."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01453-z"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01394"},{"key":"e_1_3_2_2_15_1","unstructured":"Geoffrey Hinton Oriol Vinyals Jeff Dean etal 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 Vol. 2 7 (2015).  Geoffrey Hinton Oriol Vinyals Jeff Dean et al. 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 Vol. 2 7 (2015)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00650"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"e_1_3_2_2_18_1","volume-title":"Nature","volume":"521","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun , Yoshua Bengio , and Geoffrey Hinton . 2015 . Deep learning . Nature , Vol. 521 , 7553 (2015), 436--444. Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature, Vol. 521, 7553 (2015), 436--444."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220033"},{"key":"e_1_3_2_2_20_1","volume-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv Preprint arXiv:1707.01926","author":"Li Yaguang","year":"2017","unstructured":"Yaguang Li , Rose Yu , Cyrus Shahabi , and Yan Liu . 2017. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv Preprint arXiv:1707.01926 ( 2017 ). Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu. 2017. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv Preprint arXiv:1707.01926 (2017)."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/3430915.3442433"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403281"},{"key":"e_1_3_2_2_24_1","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","volume":"26","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov , Ilya Sutskever , Kai Chen , Greg S Corrado , and Jeff Dean . 2013 . Distributed representations of words and phrases and their compositionality . Advances in Neural Information Processing Systems , Vol. 26 (2013), 3111 -- 3119 . Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems , Vol. 26 (2013), 3111--3119.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_25_1","volume-title":"Adversarial training methods for semi-supervised text classification. arXiv Preprint arXiv:1605.07725","author":"Miyato Takeru","year":"2016","unstructured":"Takeru Miyato , Andrew M Dai , and Ian Goodfellow . 2016. Adversarial training methods for semi-supervised text classification. arXiv Preprint arXiv:1605.07725 ( 2016 ). Takeru Miyato, Andrew M Dai, and Ian Goodfellow. 2016. Adversarial training methods for semi-supervised text classification. arXiv Preprint arXiv:1605.07725 (2016)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.01.012"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467172"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2884462"},{"key":"e_1_3_2_2_29_1","first-page":"2994","article-title":"Continual learning with deep generative replay","volume":"30","author":"Shin Hanul","year":"2017","unstructured":"Hanul Shin , Jung Kwon Lee , Jaehong Kim , and Jiwon Kim . 2017 . Continual learning with deep generative replay . Advances in Neural Information Processing Systems , Vol. 30 (2017), 2994 -- 3003 . Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim. 2017. Continual learning with deep generative replay. Advances in Neural Information Processing Systems , Vol. 30 (2017), 2994--3003.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330724"},{"key":"e_1_3_2_2_31_1","first-page":"6000","article-title":"Attention is all you need","volume":"30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan N Gomez , \u0141ukasz Kaiser , and Illia Polosukhin . 2017 . Attention is all you need . Advances in Neural Information Processing Systems , Vol. 30 (2017), 6000 -- 6010 . Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in Neural Information Processing Systems , Vol. 30 (2017), 6000--6010.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3293318"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539336"},{"key":"e_1_3_2_2_34_1","volume-title":"Exploring the generalizability of spatio-temporal traffic prediction: meta-modeling and an analytic framework","author":"Wang Leye","year":"2021","unstructured":"Leye Wang , Di Chai , Xuanzhe Liu , Liyue Chen , and Kai Chen . 2021a. Exploring the generalizability of spatio-temporal traffic prediction: meta-modeling and an analytic framework . IEEE Transactions on Knowledge and Data Engineering ( 2021 ). Leye Wang, Di Chai, Xuanzhe Liu, Liyue Chen, and Kai Chen. 2021a. Exploring the generalizability of spatio-temporal traffic prediction: meta-modeling and an analytic framework. IEEE Transactions on Knowledge and Data Engineering (2021)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482117"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623656"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219900"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.10.037"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1002\/nav.21872"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330865"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3389771"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2517351.2517361"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3453842","article-title":"Exploiting Real-time Search Engine Queries for Earthquake Detection: A Summary of Results","volume":"39","author":"Zhang Qi","year":"2021","unstructured":"Qi Zhang , Hengshu Zhu , Qi Liu , Enhong Chen , and Hui Xiong . 2021 . Exploiting Real-time Search Engine Queries for Earthquake Detection: A Summary of Results . ACM Transactions on Information Systems (TOIS) , Vol. 39 , 3 (2021), 1 -- 32 . Qi Zhang, Hengshu Zhu, Qi Liu, Enhong Chen, and Hui Xiong. 2021. Exploiting Real-time Search Engine Queries for Earthquake Detection: A Summary of Results. ACM Transactions on Information Systems (TOIS), Vol. 39, 3 (2021), 1--32.","journal-title":"ACM Transactions on Information Systems (TOIS)"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3432192"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2743025"}],"event":{"name":"KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Long Beach CA USA","acronym":"KDD '23","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599842","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3580305.3599842","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:23Z","timestamp":1750182563000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599842"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,4]]},"references-count":45,"alternative-id":["10.1145\/3580305.3599842","10.1145\/3580305"],"URL":"https:\/\/doi.org\/10.1145\/3580305.3599842","relation":{},"subject":[],"published":{"date-parts":[[2023,8,4]]},"assertion":[{"value":"2023-08-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}