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  • Zhang Y, Jiang Y and Alireza J. (2023). Mutual Supervised Fusion & Transfer Learning with Interpretable Linguistic Meaning for Social Data Analytics. ACM Transactions on Asian and Low-Resource Language Information Processing. 22:5. (1-20). Online publication date: 31-May-2023.

    https://doi.org/10.1145/3568675

  • Wang L, Zhang L, Yin M, Hao Z, Cai R and Wen W. (2022). Double embedding-transfer-based multi-view spectral clustering. Expert Systems with Applications. 10.1016/j.eswa.2022.118374. 210. (118374). Online publication date: 1-Dec-2022.

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  • Yu Z, Wang D, Meng X and Chen C. Clustering Ensemble Based on Hybrid Multiview Clustering. IEEE Transactions on Cybernetics. 10.1109/TCYB.2020.3034157. 52:7. (6518-6530).

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  • Wang Q, Guo B, Ouyang Y, Cheng L, Wang L, Yu Z and Liu H. Learning Shared Mobility-Aware Knowledge for Multiple Urban Travel Demands. IEEE Internet of Things Journal. 10.1109/JIOT.2021.3115174. 9:9. (7025-7035).

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  • Zhen L, Hu P, Peng X, Goh R and Zhou J. Deep Multimodal Transfer Learning for Cross-Modal Retrieval. IEEE Transactions on Neural Networks and Learning Systems. 10.1109/TNNLS.2020.3029181. 33:2. (798-810).

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  • Yan X, Ma A, Yang J, Zhu L, Jing H, Bollinger J and He Q. Contextual Skill Proficiency via Multi-task Learning at LinkedIn. Proceedings of the 30th ACM International Conference on Information & Knowledge Management. (4273-4282).

    https://doi.org/10.1145/3459637.3481904

  • Wan Y, Sun S and Zeng C. Adaptive Similarity Embedding for Unsupervised Multi-View Feature Selection. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2020.2969860. 33:10. (3338-3350).

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  • Wang F, Li W and Xu D. Cross-Dataset Point Cloud Recognition Using Deep-Shallow Domain Adaptation Network. IEEE Transactions on Image Processing. 10.1109/TIP.2021.3092818. 30. (7364-7377).

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  • Zhuang F, Qi Z, Duan K, Xi D, Zhu Y, Zhu H, Xiong H and He Q. A Comprehensive Survey on Transfer Learning. Proceedings of the IEEE. 10.1109/JPROC.2020.3004555. 109:1. (43-76).

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  • Wang D, Lu C, Wu J, Liu H, Zhang W, Zhuang F and Zhang H. Softly Associative Transfer Learning for Cross-Domain Classification. IEEE Transactions on Cybernetics. 10.1109/TCYB.2019.2891577. 50:11. (4709-4721).

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  • Zhang W, Li R, Zeng T, Sun Q, Kumar S, Ye J and Ji S. Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. IEEE Transactions on Big Data. 10.1109/TBDATA.2016.2573280. 6:2. (322-333).

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  • Mitra S, Hasanuzzaman M and Saha S. (2020). A Unified Multi-view Clustering Algorithm Using Multi-objective Optimization Coupled with Generative Model. ACM Transactions on Knowledge Discovery from Data. 14:1. (1-31). Online publication date: 29-Feb-2020.

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  • Zhang W, Xu D, Ouyang W and Li W. Self-Paced Collaborative and Adversarial Network for Unsupervised Domain Adaptation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 10.1109/TPAMI.2019.2962476. (1-1).

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  • Sun S, Mao L, Dong Z and Wu L. (2019). Multiview Transfer Learning and Multitask Learning. Multiview Machine Learning. 10.1007/978-981-13-3029-2_7. (85-104).

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  • Easterling D, Watson L and Ramakrishnan N. (2018). Probability-one homotopy methods for constrained clustering. Journal of Computational and Applied Mathematics. 10.1016/j.cam.2018.04.035. 343. (602-618). Online publication date: 1-Dec-2018.

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  • Dong X, Wu F, Jing X and Wu S. (2018). Multi-view Intact Discriminant Space Learning for Image Classification. Neural Processing Letters. 10.1007/s11063-018-9951-0.

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  • Li W, Chen L, Xu D and Van Gool L. Visual Recognition in RGB Images and Videos by Learning from RGB-D Data. IEEE Transactions on Pattern Analysis and Machine Intelligence. 10.1109/TPAMI.2017.2734890. 40:8. (2030-2036).

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  • Zhang L, Zhao Y, Zhu Z, Shen D and Ji S. Multi-View Missing Data Completion. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2018.2791607. 30:7. (1296-1309).

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  • Diasse A and Li Z. Big Cities transfer learning. Proceedings of the 2018 10th International Conference on Machine Learning and Computing. (312-321).

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  • Niu L, Li W, Xu D and Cai J. An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition. IEEE Transactions on Neural Networks and Learning Systems. 10.1109/TNNLS.2016.2615469. 29:2. (259-272).

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  • Niu L, Xu X, Chen L, Duan L and Xu D. Action and Event Recognition in Videos by Learning From Heterogeneous Web Sources. IEEE Transactions on Neural Networks and Learning Systems. 10.1109/TNNLS.2016.2518700. 28:6. (1290-1304).

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  • Ghosh S and Ghosh S. Modeling of Human Movement Behavioral Knowledge from GPS Traces for Categorizing Mobile Users. Proceedings of the 26th International Conference on World Wide Web Companion. (51-58).

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  • Jiang Y, Deng Z, Chung F and Wang S. Realizing Two-View TSK Fuzzy Classification System by Using Collaborative Learning. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 10.1109/TSMC.2016.2577558. 47:1. (145-160).

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  • Yu L, Yang , Huang Z, Wang P, Song J and Shen H. (2016). Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents. IEEE Transactions on Image Processing. 25:12. (5689-5701). Online publication date: 1-Dec-2016.

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  • Zhang N, Chen H, Chen J and Chen X. (2016). Social Media Meets Big Urban Data. Computational Intelligence and Neuroscience. 2016. (6). Online publication date: 1-Sep-2016.

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  • Wei Y, Zheng Y and Yang Q. Transfer Knowledge between Cities. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (1905-1914).

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  • Chao Lan , Yujie Deng , Xiaoli Li and Jun Huan . (2016). Co-regularized least square regression for multi-view multi-class classification 2016 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN.2016.7727218. 978-1-5090-0620-5. (342-347).

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  • Pan J, Hu X, Li P, Li H, He W, Zhang Y and Lin Y. (2016). Domain adaptation via Multi-Layer Transfer Learning. Neurocomputing. 190:C. (10-24). Online publication date: 19-May-2016.

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  • Zhu X, Li X and Zhang S. Block-Row Sparse Multiview Multilabel Learning for Image Classification. IEEE Transactions on Cybernetics. 10.1109/TCYB.2015.2403356. 46:2. (450-461).

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  • Motiian S and Doretto G. (2016). Information Bottleneck Domain Adaptation with Privileged Information for Visual Recognition. Computer Vision – ECCV 2016. 10.1007/978-3-319-46478-7_39. (630-647).

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  • Niu L, Li W and Xu D. Multi-view Domain Generalization for Visual Recognition. Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV). (4193-4201).

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  • Zhu X, Xie Q, Zhu Y, Liu X and Zhang S. (2015). Multi-view multi-sparsity kernel reconstruction for multi-class image classification. Neurocomputing. 10.1016/j.neucom.2014.08.106. 169. (43-49). Online publication date: 1-Dec-2015.

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  • Zhang Q and Hua G. Multi-View Visual Recognition of Imperfect Testing Data. Proceedings of the 23rd ACM international conference on Multimedia. (561-570).

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  • Easterling D, Watson L and Ramakrishnan N. An improved probability-one homotopy map for tracking constrained clustering solutions. Proceedings of the Symposium on High Performance Computing. (233-240).

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  • Zheng Y. Methodologies for Cross-Domain Data Fusion: An Overview. IEEE Transactions on Big Data. 10.1109/TBDATA.2015.2465959. 1:1. (16-34).

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  • Zhang Q, Hua G, Liu W, Liu Z and Zhang Z. (2015). Can Visual Recognition Benefit from Auxiliary Information in Training?. Computer Vision – ACCV 2014. 10.1007/978-3-319-16865-4_5. (65-80).

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  • Yang H and He J. Learning with dual heterogeneity. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. (582-590).

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  • Fang Z and Zhang Z. Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification. Proceedings of the 2014 22nd International Conference on Pattern Recognition. (3927-3932).

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  • Tan B, Zhong E, Xiang E and Yang Q. (2014). Multi-transfer. Statistical Analysis and Data Mining. 7:4. (282-293). Online publication date: 1-Aug-2014.

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  • Tan Q, Deng H and Yang P. (2014). Knowledge transfer across different domain data with multiple views. Neural Computing and Applications. 25:1. (15-23). Online publication date: 1-Jul-2014.

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  • Chen L, Li W and Xu D. Recognizing RGB Images by Learning from RGB-D Data. Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. (1418-1425).

    https://doi.org/10.1109/CVPR.2014.184

  • Gao W and Yang P. Democracy is good for ranking. Proceedings of the 7th ACM international conference on Web search and data mining. (63-72).

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  • Yang P and Gao W. (2014). Information-theoretic multi-view domain adaptation. Journal of Artificial Intelligence Research. 49:1. (501-525). Online publication date: 1-Jan-2014.

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  • Garcke J and Vanck T. (2014). Importance Weighted Inductive Transfer Learning for Regression. Machine Learning and Knowledge Discovery in Databases. 10.1007/978-3-662-44848-9_30. (466-481).

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  • Yang P, Gao W, Tan Q and Wong K. (2013). A link-bridged topic model for cross-domain document classification. Information Processing & Management. 10.1016/j.ipm.2013.05.002. 49:6. (1181-1193). Online publication date: 1-Nov-2013.

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  • Fang Z and Zhang Z. Discriminative feature selection for multi-view cross-domain learning. Proceedings of the 22nd ACM international conference on Information & Knowledge Management. (1321-1330).

    https://doi.org/10.1145/2505515.2505532

  • Zhang D, He J and Lawrence R. MI2LS. Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. (149-157).

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  • Chen L, Duan L and Xu D. Event Recognition in Videos by Learning from Heterogeneous Web Sources. Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. (2666-2673).

    https://doi.org/10.1109/CVPR.2013.344

  • Zhuang F, Luo P, Du C, He Q and Shi Z. Triplex transfer learning. Proceedings of the sixth ACM international conference on Web search and data mining. (425-434).

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  • Fang Z and Zhang Z. Simultaneously Combining Multi-view Multi-label Learning with Maximum Margin Classification. Proceedings of the 2012 IEEE 12th International Conference on Data Mining. (864-869).

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  • He J and Zhu Y. Hierarchical Multi-task Learning with Application to Wafer Quality Prediction. Proceedings of the 2012 IEEE 12th International Conference on Data Mining. (290-298).

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  • Yang P, Gao W, Tan Q and Wong K. Information-theoretic multi-view domain adaptation. Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2. (270-274).

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