{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:21:38Z","timestamp":1740108098559,"version":"3.37.3"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"24","license":[{"start":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T00:00:00Z","timestamp":1715472000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T00:00:00Z","timestamp":1715472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21A20472"],"award-info":[{"award-number":["U21A20472"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276065"],"award-info":[{"award-number":["62276065"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Plan of China","award":["2021YFB3600503"],"award-info":[{"award-number":["2021YFB3600503"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s00521-024-09865-x","type":"journal-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T19:01:34Z","timestamp":1715540494000},"page":"15027-15044","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["IMPRL-Net: interpretable multi-view proximity representation learning network"],"prefix":"10.1007","volume":"36","author":[{"given":"Shiyang","family":"Lan","sequence":"first","affiliation":[]},{"given":"Zihan","family":"Fang","sequence":"additional","affiliation":[]},{"given":"Shide","family":"Du","sequence":"additional","affiliation":[]},{"given":"Zhiling","family":"Cai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5195-9682","authenticated-orcid":false,"given":"Shiping","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,12]]},"reference":[{"issue":"5","key":"9865_CR1","doi-asserted-by":"crossref","first-page":"3883","DOI":"10.1007\/s00521-022-07923-w","volume":"35","author":"X Wei","year":"2023","unstructured":"Wei X, Zhang Y, Wang H (2023) Joint semantic embedding with structural knowledge and entity description for knowledge representation learning. Neural Comput Appl 35(5):3883\u20133902","journal-title":"Neural Comput Appl"},{"key":"9865_CR2","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.inffus.2022.08.014","volume":"89","author":"Q Zheng","year":"2023","unstructured":"Zheng Q, Zhu J, Li Z, Tian Z, Li C (2023) Comprehensive multi-view representation learning. Inf Fusion 89:198\u2013209","journal-title":"Inf Fusion"},{"key":"9865_CR3","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1109\/TMM.2021.3121567","volume":"25","author":"W Lu","year":"2023","unstructured":"Lu W, Li D, Nie L, Jing P, Su Y (2023) Learning dual low-rank representation for multi-label micro-video classification. IEEE Trans Multimedia 25:77\u201389","journal-title":"IEEE Trans Multimedia"},{"key":"9865_CR4","first-page":"1","volume":"135","author":"T-S Nguyen","year":"2023","unstructured":"Nguyen T-S, Luong M, Kaaniche M, Ngo LH, Beghdadi A (2023) A novel multi-branch wavelet neural network for sparse representation based object classification. Pattern Recogn 135:1\u201311","journal-title":"Pattern Recogn"},{"key":"9865_CR5","first-page":"1","volume":"36","author":"Z Wu","year":"2023","unstructured":"Wu Z, Zhang Z, Fan J (2023) Graph convolutional kernel machine versus graph convolutional networks. Adv Neural Inf Process Syst 36:1\u201314","journal-title":"Adv Neural Inf Process Syst"},{"issue":"2","key":"9865_CR6","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1007\/s00521-021-06581-8","volume":"34","author":"D Skiadopoulou","year":"2022","unstructured":"Skiadopoulou D, Likas A (2022) Face clustering using a weighted combination of deep representations. Neural Comput Appl 34(2):995\u20131006","journal-title":"Neural Comput Appl"},{"issue":"2","key":"9865_CR7","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1109\/TCSVT.2022.3207484","volume":"33","author":"T Wu","year":"2023","unstructured":"Wu T (2023) Online tensor low-rank representation for streaming data clustering. IEEE Trans Circuits Syst Video Technol 33(2):602\u2013617","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"9865_CR8","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.107857","volume":"132","author":"M Haris","year":"2024","unstructured":"Haris M, Yusoff Y, Zain AM, Khattak AS, Hussain SF (2024) Breaking down multi-view clustering: a comprehensive review of multi-view approaches for complex data structures. Eng Appl Artif Intell 132:107857","journal-title":"Eng Appl Artif Intell"},{"issue":"4","key":"9865_CR9","first-page":"4447","volume":"45","author":"Y Lin","year":"2023","unstructured":"Lin Y, Gou Y, Liu X, Bai J, Lv J, Peng X (2023) Dual contrastive prediction for incomplete multi-view representation learning. IEEE Trans Pattern Anal Mach Intell 45(4):4447\u20134461","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9865_CR10","unstructured":"Zhang W, Zhang X, Deng H, Zhang M (2022) Multi-instance causal representation learning for instance label prediction and out-of-distribution generalization. In: Proceedings of the advances in neural information processing systems, pp 34940\u201334953"},{"issue":"6","key":"9865_CR11","doi-asserted-by":"publisher","first-page":"4437","DOI":"10.1007\/s00521-021-06599-y","volume":"34","author":"Xiaodong Jia","year":"2022","unstructured":"Jia Xiaodong, Jing Xiao-Yuan, Zhu Xiaoke, Cai Ziyun, Hu Chang-Hui (2022) Co-embedding: a semi-supervised multi-view representation learning approach. Neural Comput Appl 34(6):4437\u20134457. https:\/\/doi.org\/10.1007\/s00521-021-06599-y","journal-title":"Neural Comput Appl"},{"key":"9865_CR12","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1016\/j.inffus.2022.11.006","volume":"91","author":"Dan Li","year":"2023","unstructured":"Li Dan, Wang Haibao, Wang Yufeng, Wang Shengpei (2023) Instance-wise multi-view representation learning. Inf Fusion 91:612\u2013622. https:\/\/doi.org\/10.1016\/j.inffus.2022.11.006","journal-title":"Inf Fusion"},{"key":"9865_CR13","doi-asserted-by":"crossref","first-page":"2461","DOI":"10.1109\/TMM.2021.3081930","volume":"24","author":"Z Li","year":"2022","unstructured":"Li Z, Tang C, Liu X, Zheng X, Zhang W, Zhu E (2022) Consensus graph learning for multi-view clustering. IEEE Trans Multimedia 24:2461\u20132472","journal-title":"IEEE Trans Multimedia"},{"key":"9865_CR14","first-page":"1","volume":"277","author":"X Niu","year":"2023","unstructured":"Niu X, Zhang C, Ma Y, Hu L, Zhang J (2023) A multi-view subspace representation learning approach powered by subspace transformation relationship. Knowl Based Syst 277:1\u20138","journal-title":"Knowl Based Syst"},{"issue":"5","key":"9865_CR15","doi-asserted-by":"crossref","first-page":"2399","DOI":"10.1109\/TIP.2018.2877937","volume":"28","author":"M Cheng","year":"2019","unstructured":"Cheng M, Jing L, Ng MK (2019) Tensor-based low-dimensional representation learning for multi-view clustering. IEEE Trans Image Process 28(5):2399\u20132414","journal-title":"IEEE Trans Image Process"},{"key":"9865_CR16","doi-asserted-by":"crossref","unstructured":"Zhang C, Hu Q, Fu H, Zhu P, Cao X (2017) Latent multi-view subspace clustering. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 4279\u20134287","DOI":"10.1109\/CVPR.2017.461"},{"key":"9865_CR17","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/j.ins.2023.01.071","volume":"626","author":"Z Fang","year":"2023","unstructured":"Fang Z, Du S, Lin X, Yang J, Wang S, Shi Y (2023) Dbo-net: differentiable bi-level optimization network for multi-view clustering. Inf Sci 626:572\u2013585","journal-title":"Inf Sci"},{"issue":"14","key":"9865_CR18","doi-asserted-by":"crossref","first-page":"10403","DOI":"10.1007\/s00521-019-04577-z","volume":"32","author":"R Lu","year":"2020","unstructured":"Lu R, Liu J, Lian S, Zuo X (2020) Multi-view representation learning in multi-task scene. Neural Comput Appl 32(14):10403\u201310422","journal-title":"Neural Comput Appl"},{"key":"9865_CR19","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.neunet.2023.02.026","volume":"162","author":"B Han","year":"2023","unstructured":"Han B, Wei Y, Wang Q, Wan S (2023) Dual adaptive learning multi-task multi-view for graph network representation learning. Neural Netw 162:297\u2013308","journal-title":"Neural Netw"},{"key":"9865_CR20","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.neunet.2023.09.006","volume":"168","author":"Y Chen","year":"2023","unstructured":"Chen Y, Wu Z, Chen Z, Dong M, Wang S (2023) Joint learning of feature and topology for multi-view graph convolutional network. Neural Netw 168:161\u2013170","journal-title":"Neural Netw"},{"key":"9865_CR21","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3374579","author":"J Lu","year":"2024","unstructured":"Lu J, Wu Z, Zhong L, Chen Z, Zhao H, Wang S (2024) Generative essential graph convolutional network for multi-view semi-supervised classification. IEEE Trans Multimedia. https:\/\/doi.org\/10.1109\/TMM.2024.3374579","journal-title":"IEEE Trans Multimedia"},{"issue":"7","key":"9865_CR22","doi-asserted-by":"crossref","first-page":"7082","DOI":"10.1109\/TKDE.2022.3192686","volume":"35","author":"S Huang","year":"2022","unstructured":"Huang S, Tsang IW, Xu Z, Lv J (2022) Latent representation guided multi-view clustering. IEEE Trans Knowl Data Eng 35(7):7082\u20137087","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9865_CR23","first-page":"3513","volume":"34","author":"M-S Chen","year":"2020","unstructured":"Chen M-S, Huang L, Wang C-D, Huang D (2020) Multi-view clustering in latent embedding space. Proc AAAI Conf Artif Intell 34:3513\u20133520","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"9865_CR24","first-page":"7462","volume":"36","author":"W Liang","year":"2022","unstructured":"Liang W, Liu X, Zhou S, Liu J, Wang S, Zhu E (2022) Robust graph-based multi-view clustering. Proc AAAI Conf Artif Intell 36:7462\u20137469","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"9865_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3201964","author":"S Huang","year":"2022","unstructured":"Huang S, Tsang IW, Xu Z, Lv J (2022) Cgdd: multiview graph clustering via cross-graph diversity detection. IEEE Trans Neural Netw Learn Syst. https:\/\/doi.org\/10.1109\/TNNLS.2022.3201964","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9865_CR26","first-page":"7576","volume":"36","author":"S Liu","year":"2022","unstructured":"Liu S, Wang S, Zhang P, Xu K, Liu X, Zhang C, Gao F (2022) Efficient one-pass multi-view subspace clustering with consensus anchors. Proc AAAI Conf Artif Intell 36:7576\u20137584","journal-title":"Proc AAAI Conf Artif Intell"},{"issue":"4","key":"9865_CR27","doi-asserted-by":"crossref","first-page":"3203","DOI":"10.1007\/s00521-022-07864-4","volume":"35","author":"K Xu","year":"2023","unstructured":"Xu K, Tang K, Su Z (2023) Deep multi-view subspace clustering via structure-preserved multi-scale features fusion. Neural Comput Appl 35(4):3203\u20133219","journal-title":"Neural Comput Appl"},{"key":"9865_CR28","doi-asserted-by":"crossref","unstructured":"Xu J, Tang H, Ren Y, Peng L, Zhu X, He L (2022) Multi-level feature learning for contrastive multi-view clustering. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 16051\u201316060","DOI":"10.1109\/CVPR52688.2022.01558"},{"key":"9865_CR29","doi-asserted-by":"crossref","first-page":"3182","DOI":"10.1109\/TMM.2021.3094296","volume":"24","author":"W Xia","year":"2022","unstructured":"Xia W, Wang Q, Gao Q, Zhang X, Gao X (2022) Self-supervised graph convolutional network for multi-view clustering. IEEE Trans Multimedia 24:3182\u20133192","journal-title":"IEEE Trans Multimedia"},{"key":"9865_CR30","first-page":"348","volume":"101","author":"X Bo","year":"2019","unstructured":"Bo X, Kang Z, Zhao Z, Su Y, Chen W (2019) Latent multi-view semi-supervised classification. Proc Asian Conf Mach Learn 101:348\u2013362","journal-title":"Proc Asian Conf Mach Learn"},{"issue":"7","key":"9865_CR31","first-page":"3236","volume":"29","author":"J Wu","year":"2017","unstructured":"Wu J, Pan S, Zhu X, Zhang C, Philip SY (2017) Multiple structure-view learning for graph classification. IEEE Trans Neural Netw Learn Syst 29(7):3236\u20133251","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9865_CR32","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.inffus.2020.10.022","volume":"68","author":"L Houthuys","year":"2021","unstructured":"Houthuys L, Suykens JA (2021) Tensor-based restricted kernel machines for multi-view classification. Inf Fusion 68:54\u201366","journal-title":"Inf Fusion"},{"key":"9865_CR33","doi-asserted-by":"crossref","unstructured":"Liu C, Wen J, Luo X, Huang C, Wu Z, Xu Y (2023) Dicnet: deep instance-level contrastive network for double incomplete multi-view multi-label classification. In: Proceedings of the AAAI conference on artificial intelligence, pp 8807\u20138815","DOI":"10.1609\/aaai.v37i7.26059"},{"key":"9865_CR34","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.ins.2022.01.013","volume":"591","author":"F Wu","year":"2022","unstructured":"Wu F, Jing X-Y, Wei P, Lan C, Ji Y, Jiang G-P, Huang Q (2022) Semi-supervised multi-view graph convolutional networks with application to webpage classification. Inf Sci 591:142\u2013154","journal-title":"Inf Sci"},{"key":"9865_CR35","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.patrec.2021.08.008","volume":"151","author":"X Wang","year":"2021","unstructured":"Wang X, Zhu Z, Song Y, Fu H (2021) Grnet: graph-based remodeling network for multi-view semi-supervised classification. Pattern Recogn Lett 151:95\u2013102","journal-title":"Pattern Recogn Lett"},{"issue":"9","key":"9865_CR36","doi-asserted-by":"crossref","first-page":"5042","DOI":"10.1109\/TPAMI.2021.3072422","volume":"44","author":"S Wang","year":"2022","unstructured":"Wang S, Chen Z, Du S, Lin Z (2022) Learning deep sparse regularizers with applications to multi-view clustering and semi-supervised classification. IEEE Trans Pattern Anal Mach Intell 44(9):5042\u20135055","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9865_CR37","doi-asserted-by":"crossref","first-page":"8593","DOI":"10.1109\/TMM.2023.3260649","volume":"25","author":"Z Wu","year":"2023","unstructured":"Wu Z, Lin X, Lin Z, Chen Z, Bai Y, Wang S (2023) Interpretable graph convolutional network for multi-view semi-supervised learning. IEEE Trans Multimedia 25:8593\u20138606","journal-title":"IEEE Trans Multimedia"},{"issue":"1","key":"9865_CR38","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1145\/3359786","volume":"63","author":"M Du","year":"2020","unstructured":"Du M, Liu N, Hu X (2020) Techniques for interpretable machine learning. Commun ACM 63(1):68\u201377","journal-title":"Commun ACM"},{"key":"9865_CR39","doi-asserted-by":"crossref","unstructured":"Wang S, Wu Z, Chen Y, Chen Y (2023) Beyond graph convolutional network: an interpretable regularizer-centered optimization framework. In: Proceedings of the AAAI conference on artificial intelligence, pp 4693\u20134701","DOI":"10.1609\/aaai.v37i4.25593"},{"key":"9865_CR40","doi-asserted-by":"crossref","unstructured":"Ghosh A, Mitra S, Lan A (2022) Dips: differentiable policy for sketching in recommender systems. In: Proceedings of the AAAI conference on artificial intelligence, pp 6703\u20136712","DOI":"10.1609\/aaai.v36i6.20625"},{"key":"9865_CR41","doi-asserted-by":"crossref","unstructured":"Liu A, Huang Z, Huang Z, Wang N (2021) Direct differentiable augmentation search. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 12219\u201312228","DOI":"10.1109\/ICCV48922.2021.01200"},{"key":"9865_CR42","doi-asserted-by":"crossref","unstructured":"Yang Y, Panagopoulou A, Zhou S, Jin D, Callison-Burch C, Yatskar M (2023) Language in a bottle: language model guided concept bottlenecks for interpretable image classification. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 19187\u201319197","DOI":"10.1109\/CVPR52729.2023.01839"},{"key":"9865_CR43","doi-asserted-by":"crossref","unstructured":"Giang KT, Song S, Jo S (2023) Topicfm: robust and interpretable topic-assisted feature matching. In: Proceedings of the AAAI conference on artificial intelligence, pp 2447\u20132455","DOI":"10.1609\/aaai.v37i2.25341"},{"key":"9865_CR44","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.ins.2022.07.157","volume":"610","author":"Y Wang","year":"2022","unstructured":"Wang Y, Liu J, Chang X, Rodr\u00edguez RJ, Wang J (2022) Di-aa: an interpretable white-box attack for fooling deep neural networks. Inf Sci 610:14\u201332","journal-title":"Inf Sci"},{"key":"9865_CR45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.patcog.2023.109467","volume":"139","author":"C Chen","year":"2023","unstructured":"Chen C, Li B (2023) An interpretable channel wise attention mechanism based on asymmetric and skewed gaussian distribution. Pattern Recogn 139:1\u20139","journal-title":"Pattern Recogn"},{"key":"9865_CR46","unstructured":"Cho M, Alizadeh-Vahid K, Adya S, Rastegari M (2022) Dkm: differentiable k-means clustering layer for neural network compression. In: Proceedings of the international conference on learning representationse, pp 1\u201319"},{"issue":"6","key":"9865_CR47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ipm.2023.103501","volume":"60","author":"E Jing","year":"2023","unstructured":"Jing E, Liu Y, Chai Y, Sun J, Samtani S, Jiang Y, Qian Y (2023) A deep interpretable representation learning method for speech emotion recognition. Inf Process Manag 60(6):1\u201325","journal-title":"Inf Process Manag"},{"key":"9865_CR48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cose.2023.103094","volume":"127","author":"C Tang","year":"2023","unstructured":"Tang C, Xu L, Yang B, Tang Y, Zhao D (2023) Gru-based interpretable multivariate time series anomaly detection in industrial control system. Comput Secur 127:1\u201311","journal-title":"Comput Secur"},{"key":"9865_CR49","doi-asserted-by":"crossref","unstructured":"Ko D, Choi J, Ko J, Noh S, On K-W, Kim E-S, Kim HJ (2022) Video-text representation learning via differentiable weak temporal alignment. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5016\u20135025","DOI":"10.1109\/CVPR52688.2022.00496"},{"issue":"3","key":"9865_CR50","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1109\/TIP.2018.2877335","volume":"28","author":"K Zhan","year":"2019","unstructured":"Zhan K, Nie F, Wang J, Yang Y (2019) Multiview consensus graph clustering. IEEE Trans Image Process 28(3):1261\u20131270","journal-title":"IEEE Trans Image Process"},{"issue":"6","key":"9865_CR51","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1109\/TKDE.2019.2903810","volume":"32","author":"H Wang","year":"2019","unstructured":"Wang H, Yang Y, Liu B (2019) GMC: graph-based multi-view clustering. IEEE Trans Knowl Data Eng 32(6):1116\u20131129","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9865_CR52","doi-asserted-by":"crossref","first-page":"5869","DOI":"10.1109\/TKDE.2021.3068461","volume":"12","author":"S Huang","year":"2022","unstructured":"Huang S, Tsang I, Xu Z, Lv JC (2022) Measuring diversity in graph learning: a unified framework for structured multi-view clustering. IEEE Trans Knowl Data Eng 12:5869\u20135883","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9865_CR53","first-page":"4412","volume":"34","author":"Z Kang","year":"2020","unstructured":"Kang Z, Zhou W, Zhao Z, Shao J, Han M, Xu Z (2020) Large-scale multi-view subspace clustering in linear time. Proc AAAI Conf Artif Intell 34:4412\u20134419","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"9865_CR54","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1109\/TIP.2021.3131941","volume":"31","author":"S Wang","year":"2022","unstructured":"Wang S, Liu X, Zhu X, Zhang P, Zhang Y, Gao F, Zhu E (2022) Fast parameter-free multi-view subspace clustering with consensus anchor guidance. IEEE Trans Image Process 31:556\u2013568","journal-title":"IEEE Trans Image Process"},{"key":"9865_CR55","doi-asserted-by":"crossref","unstructured":"Benton A, Khayrallah H, Gujral B, Reisinger DA, Zhang S, Arora R (2019) Deep generalized canonical correlation analysis. In: Proceedings of the workshop on representation learning for NLP, pp 1\u20136","DOI":"10.18653\/v1\/W19-4301"},{"key":"9865_CR56","doi-asserted-by":"crossref","first-page":"5352","DOI":"10.1109\/TIP.2021.3083072","volume":"30","author":"Z Huang","year":"2021","unstructured":"Huang Z, Zhou JT, Zhu H, Zhang C, Lv J, Peng X (2021) Deep spectral representation learning from multi-view data. IEEE Trans Image Process 30:5352\u20135362","journal-title":"IEEE Trans Image Process"},{"key":"9865_CR57","doi-asserted-by":"crossref","first-page":"4623","DOI":"10.1109\/TSP.2021.3101979","volume":"69","author":"S Du","year":"2021","unstructured":"Du S, Liu Z, Chen Z, Yang W, Wang S (2021) Differentiable bi-sparse multi-view co-clustering. IEEE Trans Signal Process 69:4623\u20134636","journal-title":"IEEE Trans Signal Process"},{"issue":"9","key":"9865_CR58","doi-asserted-by":"crossref","first-page":"4283","DOI":"10.1109\/TIP.2017.2717191","volume":"26","author":"H Tao","year":"2017","unstructured":"Tao H, Hou C, Nie F, Zhu J, Yi D (2017) Scalable multi-view semi-supervised classification via adaptive regression. IEEE Trans Image Process 26(9):4283\u20134296","journal-title":"IEEE Trans Image Process"},{"key":"9865_CR59","first-page":"2408","volume":"31","author":"F Nie","year":"2017","unstructured":"Nie F, Cai G, Li X (2017) Multi-view clustering and semi-supervised classification with adaptive neighbours. Proc AAAI Conf Artif Intell 31:2408\u20132414","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"9865_CR60","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.patcog.2018.11.015","volume":"88","author":"M Yang","year":"2019","unstructured":"Yang M, Deng C, Nie F (2019) Adaptive-weighting discriminative regression for multi-view classification. Pattern Recogn 88:236\u2013245","journal-title":"Pattern Recogn"},{"issue":"2","key":"9865_CR61","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1109\/TCYB.2018.2869789","volume":"50","author":"Y Xie","year":"2018","unstructured":"Xie Y, Zhang W, Qu Y, Dai L, Tao D (2018) Hyper-Laplacian regularized multilinear multiview self-representations for clustering and semisupervised learning. IEEE Trans Cybern 50(2):572\u2013586","journal-title":"IEEE Trans Cybern"},{"key":"9865_CR62","doi-asserted-by":"crossref","first-page":"6997","DOI":"10.1109\/TIP.2021.3101917","volume":"30","author":"A Huang","year":"2021","unstructured":"Huang A, Wang Z, Zheng Y, Zhao T, Lin C-W (2021) Embedding regularizer learning for multi-view semi-supervised classification. IEEE Trans Image Process 30:6997\u20137011","journal-title":"IEEE Trans Image Process"},{"key":"9865_CR63","first-page":"4691","volume":"34","author":"S Li","year":"2020","unstructured":"Li S, Li W-T, Wang W (2020) Co-gcn for multi-view semi-supervised learning. Proc AAAI Conf Artif Intell 34:4691\u20134698","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"9865_CR64","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.inffus.2023.02.013","volume":"95","author":"Z Chen","year":"2023","unstructured":"Chen Z, Fu L, Yao J, Guo W, Plant C, Wang S (2023) Learnable graph convolutional network and feature fusion for multi-view learning. Inf Fusion 95:109\u2013119","journal-title":"Inf Fusion"},{"key":"9865_CR65","unstructured":"Kipf TN, Welling M (2017) Semi-supervised classification with graph convolutional networks. In: Proceedings of the international conference on learning representationse, pp 1\u201314"},{"key":"9865_CR66","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09865-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-09865-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09865-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T10:11:59Z","timestamp":1724148719000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-09865-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,12]]},"references-count":66,"journal-issue":{"issue":"24","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["9865"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-09865-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2024,5,12]]},"assertion":[{"value":"12 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 May 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}