{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T16:18:23Z","timestamp":1780762703523,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62425605, 62472340, 62303366, 62203354"],"award-info":[{"award-number":["62425605, 62472340, 62303366, 62203354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015401","name":"Key Research and Development Projects of Shaanxi Province","doi-asserted-by":"publisher","award":["2025GH-YBXM-018, 2025CY-YBXM-041, 2024GXYBXM-122, 2022ZDLGY01-10"],"award-info":[{"award-number":["2025GH-YBXM-018, 2025CY-YBXM-041, 2024GXYBXM-122, 2022ZDLGY01-10"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017596","name":"Natural Science Basic Research Program of Shaanxi Province","doi-asserted-by":"publisher","award":["2025JC-QYXQ-040, 2025JC-YBQN-900"],"award-info":[{"award-number":["2025JC-QYXQ-040, 2025JC-YBQN-900"]}],"id":[{"id":"10.13039\/501100017596","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["YJSJ25012"],"award-info":[{"award-number":["YJSJ25012"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3755092","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T05:50:47Z","timestamp":1761371447000},"page":"1278-1287","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Beyond Equal Views: Strength-Adaptive Evidential Multi-View Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7191-7348","authenticated-orcid":false,"given":"Cai","family":"Xu","sequence":"first","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8581-5098","authenticated-orcid":false,"given":"Ziqi","family":"Wen","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4981-3427","authenticated-orcid":false,"given":"Jie","family":"Zhao","sequence":"additional","affiliation":[{"name":"Chang'an University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7622-0665","authenticated-orcid":false,"given":"Wanqing","family":"Zhao","sequence":"additional","affiliation":[{"name":"Northwest University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7821-7218","authenticated-orcid":false,"given":"Jinlong","family":"Yu","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7296-4912","authenticated-orcid":false,"given":"Haishun","family":"Chen","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2413-4698","authenticated-orcid":false,"given":"Ziyu","family":"Guan","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9767-1323","authenticated-orcid":false,"given":"Wei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Virtual category learning: A semi-supervised learning method for dense prediction with extremely limited labels","author":"Chen Changrui","year":"2024","unstructured":"Changrui Chen, Jungong Han, and Kurt Debattista. 2024. Virtual category learning: A semi-supervised learning method for dense prediction with extremely limited labels. IEEE transactions on pattern analysis and machine intelligence, Vol. 46, 8 (2024), 5595-5611."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01416"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00059"},{"key":"e_1_3_2_1_4_1","volume-title":"International Conference on Machine Learning. PMLR, 7596-7616","author":"Deng Danruo","year":"2023","unstructured":"Danruo Deng, Guangyong Chen, Yang Yu, Furui Liu, and Pheng-Ann Heng. 2023. Uncertainty estimation by fisher information-based evidential deep learning. In International Conference on Machine Learning. PMLR, 7596-7616."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3180556"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01781"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00335"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01547"},{"key":"e_1_3_2_1_9_1","volume-title":"international conference on machine learning. PMLR, 1050-1059","author":"Gal Yarin","year":"2016","unstructured":"Yarin Gal and Zoubin Ghahramani. 2016. Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In international conference on machine learning. PMLR, 1050-1059."},{"key":"e_1_3_2_1_10_1","volume-title":"A survey on uncertainty reasoning and quantification for decision making: Belief theory meets deep learning. arXiv preprint arXiv:2206.05675","author":"Guo Zhen","year":"2022","unstructured":"Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Feng Chen, Jin-Hee Cho, Qi Zhang, Lance M Kaplan, Dong H Jeong, and Audun J\u00f8sang. 2022. A survey on uncertainty reasoning and quantification for decision making: Belief theory meets deep learning. arXiv preprint arXiv:2206.05675 (2022)."},{"key":"e_1_3_2_1_11_1","volume-title":"Trusted Multi-View Classification. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=OOsR8BzCnl5","author":"Han Zongbo","year":"2021","unstructured":"Zongbo Han, Changqing Zhang, Huazhu Fu, and Joey Tianyi Zhou. 2021. Trusted Multi-View Classification. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=OOsR8BzCnl5"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3171983"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3354731"},{"key":"e_1_3_2_1_14_1","volume-title":"International conference on machine learning. PMLR, 4629-4640","author":"Izmailov Pavel","year":"2021","unstructured":"Pavel Izmailov, Sharad Vikram, Matthew D Hoffman, and Andrew Gordon Gordon Wilson. 2021. What are Bayesian neural network posteriors really like?. In International conference on machine learning. PMLR, 4629-4640."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCE46568.2020.9043106"},{"key":"e_1_3_2_1_16_1","volume-title":"Subjective logic","author":"J\u00f8sang Audun","unstructured":"Audun J\u00f8sang. 2016. Subjective logic. Vol. 3. Springer."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2021.3064943"},{"key":"e_1_3_2_1_18_1","first-page":"4447","article-title":"Dual contrastive prediction for incomplete multi-view representation learning","volume":"45","author":"Lin Yijie","year":"2022","unstructured":"Yijie Lin, Yuanbiao Gou, Xiaotian Liu, Jinfeng Bai, Jiancheng Lv, and Xi Peng. 2022. Dual contrastive prediction for incomplete multi-view representation learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45, 4 (2022), 4447-4461.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612362"},{"key":"e_1_3_2_1_20_1","volume-title":"Information recovery-driven deep incomplete multiview clustering network","author":"Liu Chengliang","year":"2023","unstructured":"Chengliang Liu, Jie Wen, Zhihao Wu, Xiaoling Luo, Chao Huang, and Yong Xu. 2023. Information recovery-driven deep incomplete multiview clustering network. IEEE Transactions on Neural Networks and Learning Systems (2023)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5922"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681297"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20724"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681404"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.121699"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462945"},{"key":"e_1_3_2_1_27_1","volume-title":"Towards maximizing the representation gap between in-domain & out-of-distribution examples. Advances in neural information processing systems","author":"Nandy Jay","year":"2020","unstructured":"Jay Nandy, Wynne Hsu, and Mong Li Lee. 2020. Towards maximizing the representation gap between in-domain & out-of-distribution examples. Advances in neural information processing systems, Vol. 33 (2020), 9239-9250."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547922"},{"key":"e_1_3_2_1_29_1","volume-title":"Deep learning for medical image processing: Overview, challenges and the future. Classification in BioApps: Automation of decision making","author":"Razzak Muhammad Imran","year":"2017","unstructured":"Muhammad Imran Razzak, Saeeda Naz, and Ahmad Zaib. 2017. Deep learning for medical image processing: Overview, challenges and the future. Classification in BioApps: Automation of decision making (2017), 323-350."},{"key":"e_1_3_2_1_30_1","volume-title":"Evidential deep learning to quantify classification uncertainty. Advances in neural information processing systems","author":"Sensoy Murat","year":"2018","unstructured":"Murat Sensoy, Lance Kaplan, and Melih Kandemir. 2018. Evidential deep learning to quantify classification uncertainty. Advances in neural information processing systems, Vol. 31 (2018)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3168279"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3423307"},{"key":"e_1_3_2_1_33_1","volume-title":"Proceedings of the NATO Big Data and Artificial Intelligence for Military Decision Making Specialists' Meeting","volume":"1","author":"Svenmarck Peter","year":"2018","unstructured":"Peter Svenmarck, Linus Luotsinen, Mattias Nilsson, and Johan Schubert. 2018. Possibilities and challenges for artificial intelligence in military applications. In Proceedings of the NATO Big Data and Artificial Intelligence for Military Decision Making Specialists' Meeting, Vol. 1."},{"key":"e_1_3_2_1_34_1","volume-title":"International conference on machine learning. PMLR, 9690-9700","author":"Amersfoort Joost Van","year":"2020","unstructured":"Joost Van Amersfoort, Lewis Smith, Yee Whye Teh, and Yarin Gal. 2020. Uncertainty estimation using a single deep deterministic neural network. In International conference on machine learning. PMLR, 9690-9700."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-42444-7"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3444320"},{"key":"e_1_3_2_1_37_1","volume-title":"Deep semisupervised class-and correlation-collapsed cross-view learning","author":"Wang Xu","year":"2020","unstructured":"Xu Wang, Peng Hu, Pei Liu, and Dezhong Peng. 2020. Deep semisupervised class-and correlation-collapsed cross-view learning. IEEE transactions on cybernetics, Vol. 52, 3 (2020), 1588-1601."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3070179"},{"key":"e_1_3_2_1_39_1","volume-title":"Batchensemble: an alternative approach to efficient ensemble and lifelong learning. arXiv preprint arXiv:2002.06715","author":"Wen Yeming","year":"2020","unstructured":"Yeming Wen, Dustin Tran, and Jimmy Ba. 2020. Batchensemble: an alternative approach to efficient ensemble and lifelong learning. arXiv preprint arXiv:2002.06715 (2020)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01903"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612527"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i14.29546"},{"key":"e_1_3_2_1_43_1","volume-title":"Trusted Multi-view Learning with Label Noise. arXiv preprint arXiv:2404.11944","author":"Xu Cai","year":"2024","unstructured":"Cai Xu, Yilin Zhang, Ziyu Guan, and Wei Zhao. 2024b. Trusted Multi-view Learning with Label Noise. arXiv preprint arXiv:2404.11944 (2024)."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102643"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.12.007"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3235374"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107960"},{"key":"e_1_3_2_1_48_1","volume-title":"A multi-view deep learning framework for EEG seizure detection","author":"Yuan Ye","year":"2018","unstructured":"Ye Yuan, Guangxu Xun, Kebin Jia, and Aidong Zhang. 2018. A multi-view deep learning framework for EEG seizure detection. IEEE journal of biomedical and health informatics, Vol. 23, 1 (2018), 83-94."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.12.029"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02201"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611965"}],"event":{"name":"MM '25: The 33rd ACM International Conference on Multimedia","location":"Dublin Ireland","acronym":"MM '25","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 33rd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746027.3755092","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T19:21:24Z","timestamp":1765308084000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3755092"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":51,"alternative-id":["10.1145\/3746027.3755092","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3755092","relation":{},"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}