{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,20]],"date-time":"2025-07-20T22:45:19Z","timestamp":1753051519182,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":54,"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\/3534678.3539262","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:12Z","timestamp":1660331172000},"page":"1558-1566","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Active Model Adaptation Under Unknown Shift"],"prefix":"10.1145","author":[{"given":"Jie-Jing","family":"Shao","sequence":"first","affiliation":[{"name":"Nanjing University, Nanjing, China"}]},{"given":"Yunlu","family":"Xu","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute, Hangzhou, China"}]},{"given":"Zhanzhan","family":"Cheng","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute, Hangzhou, China"}]},{"given":"Yu-Feng","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Concrete Problems in AI Safety. CoRR","author":"Amodei Dario","year":"2016","unstructured":"Dario Amodei, Chris Olah, Jacob Steinhardt, Paul F. Christiano, John Schulman, and Dan Man\u00e9. 2016. Concrete Problems in AI Safety. CoRR (2016)."},{"key":"e_1_3_2_2_2_1","unstructured":"Mahsa Baktashmotlagh Masoud Faraki Tom Drummond and Mathieu Salzmann. 2019. Learning Factorized Representations for Open-Set Domain Adaptation. In ICLR."},{"key":"e_1_3_2_2_3_1","volume-title":"Bartlett and Shahar Mendelson","author":"Peter","year":"2002","unstructured":"Peter L. Bartlett and Shahar Mendelson. 2002. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. JMLR (2002)."},{"key":"e_1_3_2_2_4_1","volume-title":"Boult","author":"Bendale Abhijit","year":"2016","unstructured":"Abhijit Bendale and Terrance E. Boult. 2016. Towards Open Set Deep Networks. In CVPR."},{"key":"e_1_3_2_2_5_1","volume-title":"Semi-Supervised Novelty Detection. JMLR","author":"Blanchard Gilles","year":"2010","unstructured":"Gilles Blanchard, Gyemin Lee, and Clayton Scott. 2010. Semi-Supervised Novelty Detection. JMLR (2010)."},{"key":"e_1_3_2_2_6_1","unstructured":"Pau Panareda Busto and Juergen Gall. 2017. Open Set Domain Adaptation. In ICCV."},{"key":"e_1_3_2_2_7_1","volume":"200","author":"Dasgupta Sanjoy","unstructured":"Sanjoy Dasgupta and Daniel J. Hsu. 2008. Hierarchical sampling for active learning. In ICML.","journal-title":"Daniel J. Hsu."},{"key":"e_1_3_2_2_8_1","unstructured":"Antoine de Mathelin Mathilde Mougeot and Nicolas Vayatis. 2022. DiscrepancyBased Active Learning for Domain Adaptation. In ICLR."},{"key":"e_1_3_2_2_9_1","unstructured":"Marthinus Christoffel du Plessis Gang Niu and Masashi Sugiyama. 2014. Analysis of Learning from Positive and Unlabeled Data. In NIPS."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"crossref","unstructured":"Bo Fu Zhangjie Cao Jianmin Wang and Mingsheng Long. 2021. Transferable Query Selection for Active Domain Adaptation. In CVPR.","DOI":"10.1109\/CVPR46437.2021.00719"},{"key":"e_1_3_2_2_11_1","volume-title":"Lempitsky","author":"Ganin Yaroslav","year":"2015","unstructured":"Yaroslav Ganin and Victor S. Lempitsky. 2015. Unsupervised Domain Adaptation by Backpropagation. In ICML."},{"key":"e_1_3_2_2_12_1","volume-title":"Lempitsky","author":"Ganin Yaroslav","year":"2016","unstructured":"Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, Fran\u00e7ois Laviolette, Mario Marchand, and Victor S. Lempitsky. 2016. Domain-Adversarial Training of Neural Networks. JMLR (2016)."},{"key":"e_1_3_2_2_13_1","volume-title":"Collective Decision for Open Set Recognition. TKDE","author":"Geng Chuanxing","year":"2022","unstructured":"Chuanxing Geng and Songcan Chen. 2022. Collective Decision for Open Set Recognition. TKDE (2022)."},{"key":"e_1_3_2_2_14_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR."},{"key":"e_1_3_2_2_15_1","unstructured":"Judy Hoffman Eric Tzeng Taesung Park Jun-Yan Zhu Phillip Isola Kate Saenko Alexei A. Efros and Trevor Darrell. 2018. CyCADA: Cycle-Consistent Adversarial Domain Adaptation. In ICML."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Sheng-Jun Huang Jia-Wei Zhao and Zhao-Yang Liu. 2018. Cost-Effective Training of Deep CNNs with Active Model Adaptation. In KDD.","DOI":"10.1145\/3219819.3220026"},{"key":"e_1_3_2_2_17_1","volume-title":"Nonparametric Semi-Supervised Learning of Class Proportions. CoRR","author":"Jain Shantanu","year":"2016","unstructured":"Shantanu Jain, Martha White, Michael W. Trosset, and Predrag Radivojac. 2016. Nonparametric Semi-Supervised Learning of Class Proportions. CoRR (2016)."},{"key":"e_1_3_2_2_18_1","volume-title":"Papanikolopoulos","author":"Joshi Ajay J.","year":"2012","unstructured":"Ajay J. Joshi, Fatih Porikli, and Nikolaos P. Papanikolopoulos. 2012. Scalable Active Learning for Multiclass Image Classification. TMPAI (2012)."},{"key":"e_1_3_2_2_19_1","volume-title":"Sung Ju Hwang, and Jinwoo Shin","author":"Kim Jaehyung","year":"2020","unstructured":"Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, and Jinwoo Shin. 2020. Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. In NeurIPS."},{"key":"e_1_3_2_2_20_1","volume-title":"Marthinus Christoffel du Plessis, and Masashi Sugiyama","author":"Kiryo Ryuichi","year":"2017","unstructured":"Ryuichi Kiryo, Gang Niu, Marthinus Christoffel du Plessis, and Masashi Sugiyama. 2017. Positive-Unlabeled Learning with Non-Negative Risk Estimator. In NIPS."},{"key":"e_1_3_2_2_21_1","volume-title":"Gradientbased learning applied to document recognition","author":"LeCun Yann","year":"1998","unstructured":"Yann LeCun, L\u00e9on Bottou, Yoshua Bengio, and Patrick Haffner. 1998. Gradientbased learning applied to document recognition. IEEE (1998)."},{"key":"e_1_3_2_2_22_1","volume":"200","author":"Lee Kuang-Chih","unstructured":"Kuang-Chih Lee, Jeffrey Ho, and David J. Kriegman. 2005. Acquiring Linear Subspaces for Face Recognition under Variable Lighting. TMPAI (2005).","journal-title":"David J. Kriegman."},{"key":"e_1_3_2_2_23_1","unstructured":"Kimin Lee Kibok Lee Honglak Lee and Jinwoo Shin. 2018. A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. In NeurIPS."},{"key":"e_1_3_2_2_24_1","unstructured":"Shiyu Liang Yixuan Li and R. Srikant. 2018. Enhancing The Reliability of Outof-distribution Image Detection in Neural Networks. In ICLR."},{"key":"e_1_3_2_2_25_1","volume-title":"Kai Ming Ting, and Zhi-Hua Zhou","author":"Liu Fei Tony","year":"2008","unstructured":"Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. 2008. Isolation Forest. In ICDM."},{"key":"e_1_3_2_2_26_1","unstructured":"Wei Liu Junfeng He and Shih-Fu Chang. 2010. Large Graph Construction for Scalable Semi-Supervised Learning. In ICML."},{"key":"e_1_3_2_2_27_1","volume-title":"Jordan","author":"Long Mingsheng","year":"2019","unstructured":"Mingsheng Long, Yue Cao, Zhangjie Cao, Jianmin Wang, and Michael I. Jordan. 2019. Transferable Representation Learning with Deep Adaptation Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (2019)."},{"key":"e_1_3_2_2_28_1","volume-title":"Jordan","author":"Long Mingsheng","year":"2017","unstructured":"Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I. Jordan. 2017. Deep Transfer Learning with Joint Adaptation Networks. In ICML."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46379-7_1"},{"key":"e_1_3_2_2_30_1","unstructured":"Yuval Netzer Tao Wang Adam Coates Alessandro Bissacco Bo Wu and Andrew Y Ng. 2011. Reading digits in natural images with unsupervised feature learning. (2011)."},{"key":"e_1_3_2_2_31_1","volume-title":"Domain Adaptation via Transfer Component Analysis. TNN","author":"Pan Sinno Jialin","year":"2011","unstructured":"Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, and Qiang Yang. 2011. Domain Adaptation via Transfer Component Analysis. TNN (2011)."},{"key":"e_1_3_2_2_32_1","volume-title":"A Survey on Transfer Learning. TKDE","author":"Pan Sinno Jialin","year":"2010","unstructured":"Sinno Jialin Pan and Qiang Yang. 2010. A Survey on Transfer Learning. TKDE (2010)."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"Viraj Prabhu Arjun Chandrasekaran Kate Saenko and Judy Hoffman. 2021. Active domain adaptation via clustering uncertainty-weighted embeddings. In ICCV.","DOI":"10.1109\/ICCV48922.2021.00839"},{"key":"e_1_3_2_2_34_1","volume-title":"Domain Adaptation Meets Active Learning. In NAACL HLT Workshop.","author":"Rai Piyush","year":"2010","unstructured":"Piyush Rai, Avishek Saha, Hal Daum\u00e9 III, and Suresh Venkatasubramanian. 2010. Domain Adaptation Meets Active Learning. In NAACL HLT Workshop."},{"key":"e_1_3_2_2_35_1","unstructured":"Harish G. Ramaswamy Clayton Scott and Ambuj Tewari. 2016. Mixture Proportion Estimation via Kernel Embeddings of Distributions. In ICML."},{"key":"e_1_3_2_2_36_1","volume-title":"Suresh Venkatasubramanian, and Scott L. DuVall.","author":"Saha Avishek","year":"2011","unstructured":"Avishek Saha, Piyush Rai, Hal Daum\u00e9 III, Suresh Venkatasubramanian, and Scott L. DuVall. 2011. Active Supervised Domain Adaptation. In ECML\/PKDD."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Kuniaki Saito Kohei Watanabe Yoshitaka Ushiku and Tatsuya Harada. 2018. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation. In CVPR.","DOI":"10.1109\/CVPR.2018.00392"},{"key":"e_1_3_2_2_38_1","volume-title":"Boult","author":"Scheirer Walter J.","year":"2014","unstructured":"Walter J. Scheirer, Lalit P. Jain, and Terrance E. Boult. 2014. Probability Models for Open Set Recognition. TMPAI (2014)."},{"key":"e_1_3_2_2_39_1","volume-title":"Williamson","author":"Sch\u00f6lkopf Bernhard","year":"2001","unstructured":"Bernhard Sch\u00f6lkopf, John C. Platt, John Shawe-Taylor, Alexander J. Smola, and Robert C. Williamson. 2001. Estimating the Support of a High-Dimensional Distribution. Neural Computation (2001)."},{"key":"e_1_3_2_2_40_1","unstructured":"Ozan Sener and Silvio Savarese. 2018. Active Learning for Convolutional Neural Networks: A Core-Set Approach. In ICLR."},{"key":"e_1_3_2_2_41_1","unstructured":"H. Sebastian Seung Manfred Opper and Haim Sompolinsky. 1992. Query by Committee. In COLT."},{"key":"e_1_3_2_2_42_1","unstructured":"Gabi Shalev Yossi Adi and Joseph Keshet. 2018. Out-of-Distribution Detection using Multiple Semantic Label Representations. In NeurIPS."},{"key":"e_1_3_2_2_43_1","unstructured":"Jong-Chyi Su Yi-Hsuan Tsai Kihyuk Sohn Buyu Liu Subhransu Maji and Manmohan Chandraker. 2020. Active Adversarial Domain Adaptation. In WACV."},{"key":"e_1_3_2_2_44_1","volume-title":"Borgwardt","author":"Sugiyama Mahito","year":"2013","unstructured":"Mahito Sugiyama and Karsten M. Borgwardt. 2013. Rapid Distance-Based Outlier Detection via Sampling. In NIPS."},{"key":"e_1_3_2_2_45_1","volume-title":"Keck Voon Ling, and Guohao Peng","author":"Sun Xin","year":"2020","unstructured":"Xin Sun, Zhenning Yang, Chi Zhang, Keck Voon Ling, and Guohao Peng. 2020. Conditional Gaussian Distribution Learning for Open Set Recognition. In CVPR."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"crossref","unstructured":"Eric Tzeng Judy Hoffman Kate Saenko and Trevor Darrell. 2017. Adversarial Discriminative Domain Adaptation. In CVPR.","DOI":"10.1109\/CVPR.2017.316"},{"key":"e_1_3_2_2_47_1","volume-title":"Deep Domain Confusion: Maximizing for Domain Invariance. CoRR","author":"Tzeng Eric","year":"2014","unstructured":"Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell. 2014. Deep Domain Confusion: Maximizing for Domain Invariance. CoRR (2014)."},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"crossref","unstructured":"Hemanth Venkateswara Jose Eusebio Shayok Chakraborty and Sethuraman Panchanathan. 2017. Deep hashing network for unsupervised domain adaptation. In CVPR.","DOI":"10.1109\/CVPR.2017.572"},{"key":"e_1_3_2_2_49_1","volume-title":"Patel","author":"Zhang He","year":"2017","unstructured":"He Zhang and Vishal M. Patel. 2017. Sparse Representation-Based Open Set Recognition. TMPAI (2017)."},{"key":"e_1_3_2_2_50_1","unstructured":"Lijun Zhang Shiyin Lu and Zhi-Hua Zhou. 2018. Adaptive Online Learning in Dynamic Environments. In NeurIPS."},{"key":"e_1_3_2_2_51_1","volume-title":"Jordan","author":"Zhang Yuchen","year":"2020","unstructured":"Yuchen Zhang, Mingsheng Long, Jianmin Wang, and Michael I. Jordan. 2020. On Localized Discrepancy for Domain Adaptation. CoRR (2020)."},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"crossref","unstructured":"Yu-Jie Zhang Yu-Hu Yan Peng Zhao and Zhi-Hua Zhou. 2021. Towards Enabling Learnware to Handle Unseen Jobs. In AAAI.","DOI":"10.1609\/aaai.v35i12.17309"},{"key":"e_1_3_2_2_53_1","unstructured":"Yu-Jie Zhang Peng Zhao Lanjihong Ma and Zhi-Hua Zhou. 2020. An Unbiased Risk Estimator for Learning with Augmented Classes. In NeurIPS."},{"key":"e_1_3_2_2_54_1","unstructured":"Peng Zhao Xinqiang Wang Siyu Xie Lei Guo and Zhi-Hua Zhou. 2021. Distribution-Free One-Pass Learning. TKDE (2021"}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Washington DC USA","acronym":"KDD '22"},"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\/3534678.3539262","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539262","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:59:59Z","timestamp":1750186799000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539262"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":54,"alternative-id":["10.1145\/3534678.3539262","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539262","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"}}]}}