{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T21:07:30Z","timestamp":1730322450327,"version":"3.28.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","funder":[{"name":"National Science Fund for Young Scholars","award":["No. 61702163"]},{"name":"National Key Research and Development Program of China","award":["No. 2016YFE0104600"]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,12,13]]},"DOI":"10.1145\/3375998.3376022","type":"proceedings-article","created":{"date-parts":[[2020,1,28]],"date-time":"2020-01-28T10:30:03Z","timestamp":1580207403000},"page":"19-27","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Semi-supervised Flexible Joint Distribution Adaptation"],"prefix":"10.1145","author":[{"given":"Shaofei","family":"Zang","sequence":"first","affiliation":[{"name":"School of Information Engineering, Henan University of Science and Technology, Luoyang, China"}]},{"given":"Yuhu","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China"}]},{"given":"Xuesong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China"}]},{"given":"Jianwei","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Henan University of Science and Technology, Luoyang, China"}]}],"member":"320","published-online":{"date-parts":[[2020,1,28]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Principal component analysis. Chemometrics and intelligent laboratory systems. 2, 1 (August","author":"Wold S.","year":"1987","unstructured":"Wold , S. , Esbensen , K. , & Geladi , P. 1987. Principal component analysis. Chemometrics and intelligent laboratory systems. 2, 1 (August 1987 ), 37--52. DOI= https:\/\/doi.org\/10.1016\/0169-7439(87)80084-9 10.1016\/0169-7439(87)80084-9 Wold, S., Esbensen, K., & Geladi, P. 1987. Principal component analysis. Chemometrics and intelligent laboratory systems. 2, 1 (August 1987), 37--52. DOI= https:\/\/doi.org\/10.1016\/0169-7439(87)80084-9"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-1809.1936.tb02137.x"},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the neural information processing systems (pp. 153--160)","author":"He X.","year":"2004","unstructured":"He , X. , & Niyogi , P. 2004 . Locality preserving projections . In Proceedings of the neural information processing systems (pp. 153--160) . He, X., & Niyogi, P. 2004. Locality preserving projections. In Proceedings of the neural information processing systems (pp. 153--160)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2007.4408856"},{"key":"e_1_3_2_1_5_1","first-page":"10","article-title":"A survey on transfer learning","volume":"22","author":"Pan S. J.","year":"2009","unstructured":"Pan , S. J. , & Yang , Q. 2009 . A survey on transfer learning . In Proceedings of IEEE Transactions on Knowledge and Data Engineering. 22 , 10 (October 2010). 1345--1359. DOI=10.1109\/TKDE.2009.191 Pan, S. J., & Yang, Q. 2009. A survey on transfer learning. In Proceedings of IEEE Transactions on Knowledge and Data Engineering. 22, 10 (October 2010). 1345--1359. DOI=10.1109\/TKDE.2009.191","journal-title":"Proceedings of IEEE Transactions on Knowledge and Data Engineering."},{"key":"e_1_3_2_1_6_1","first-page":"7","article-title":"Bregman divergence-based regularization for transfer subspace learning","volume":"22","author":"Si S.","year":"2009","unstructured":"Si , S. , Tao , D. , & Geng , B. 2009 . Bregman divergence-based regularization for transfer subspace learning . IEEE Transactions on Knowledge and Data Engineering. 22 , 7 (July 2010). 929--942. DOI=10.1109\/TKDE.2009.126 Si, S., Tao, D., & Geng, B. 2009. Bregman divergence-based regularization for transfer subspace learning. IEEE Transactions on Knowledge and Data Engineering. 22, 7 (July 2010). 929--942. DOI=10.1109\/TKDE.2009.126","journal-title":"IEEE Transactions on Knowledge and Data Engineering."},{"key":"e_1_3_2_1_7_1","first-page":"2066","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"Gong B.","year":"2012","unstructured":"Gong , B. , Shi , Y. , Sha , F. , & Grauman , K. 2012 . Geodesic flow kernel for unsupervised domain adaptation . In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition ( Providence, RI, USA , June 16-21, 2012), pp. 2066 -- 2073 DOI=10.1109\/CVPR.2012.6247911 Gong, B., Shi, Y., Sha, F., & Grauman, K. 2012. Geodesic flow kernel for unsupervised domain adaptation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition(Providence, RI, USA, June 16-21, 2012), pp. 2066--2073 DOI=10.1109\/CVPR.2012.6247911"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.368"},{"key":"e_1_3_2_1_9_1","unstructured":"Fernando B. Habrard A. Sebban M. & Tuytelaars T. 2014. Subspace alignment for domain adaptation. arXiv preprint arXiv:1409.5241. Fernando B. Habrard A. Sebban M. & Tuytelaars T. 2014. Subspace alignment for domain adaptation. arXiv preprint arXiv:1409.5241."},{"key":"e_1_3_2_1_10_1","article-title":"Domain adaptation via transfer component analysis","volume":"22","author":"Pan S. J.","year":"2010","unstructured":"Pan , S. J. , Tsang , I. W. , Kwok , J. T. , & Yang , Q. 2010 . Domain adaptation via transfer component analysis . IEEE Transactions on Neural Networks. 22 , 2( Feb. 2011).199--210. DOI= 10.1109\/TNN.2010.2091281 Pan, S. J., Tsang, I. W., Kwok, J. T., & Yang, Q. 2010. Domain adaptation via transfer component analysis. IEEE Transactions on Neural Networks. 22, 2(Feb. 2011).199--210. DOI= 10.1109\/TNN.2010.2091281","journal-title":"IEEE Transactions on Neural Networks."},{"key":"e_1_3_2_1_11_1","volume-title":"Integrating structured biological data by kernel maximum mean discrepancy. Bioinformatics. 22, 14(July","author":"Borgwardt K. M.","year":"2006","unstructured":"Borgwardt , K. M. , Gretton , A. , Rasch , M. J. , Kriegel , H. P. , Sch\u00f6lkopf , B. , & Smola , A. J. 2006. Integrating structured biological data by kernel maximum mean discrepancy. Bioinformatics. 22, 14(July 2006 ). e49-e57. DOI= https:\/\/doi.org\/10.1093\/bioinformatics\/btl242 10.1093\/bioinformatics Borgwardt, K. M., Gretton, A., Rasch, M. J., Kriegel, H. P., Sch\u00f6lkopf, B., & Smola, A. J. 2006. Integrating structured biological data by kernel maximum mean discrepancy. Bioinformatics. 22, 14(July 2006). e49-e57. DOI= https:\/\/doi.org\/10.1093\/bioinformatics\/btl242"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.274"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.183"},{"key":"e_1_3_2_1_14_1","article-title":"Scatter component analysis: a unified framework for domain adaptation and domain generalization","volume":"39","author":"Ghifary M.","year":"2015","unstructured":"Ghifary , M. , Balduzzi , D. , Kleijn , W. B. ,& Zhang , M. 2015 . Scatter component analysis: a unified framework for domain adaptation and domain generalization . IEEE Trans Pattern Anal Mach Intell. 39 , 7( August 2016). 1414--1430. DOI= 10.1109\/TPAMI.2016.2599532 Ghifary, M., Balduzzi, D., Kleijn, W. B.,& Zhang, M. 2015. Scatter component analysis: a unified framework for domain adaptation and domain generalization. IEEE Trans Pattern Anal Mach Intell. 39, 7(August 2016). 1414--1430. DOI= 10.1109\/TPAMI.2016.2599532","journal-title":"IEEE Trans Pattern Anal Mach Intell."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2013.2246837"},{"key":"e_1_3_2_1_16_1","volume-title":"Flexible unsupervised feature extraction for image classification. Neural Networks.115 (July","author":"Liu Y.","year":"2019","unstructured":"Liu , Y. , Nie , F. , Gao , Q. , Gao , X. , Han , J. , & Shao , L. 2019. Flexible unsupervised feature extraction for image classification. Neural Networks.115 (July 2019 ). 65--71. DOI= https:\/\/doi.org\/10.1016\/j.neunet.2019.03.008 10.1016\/j.neunet.2019.03.008 Liu, Y., Nie, F., Gao, Q., Gao, X., Han, J., & Shao, L. 2019. Flexible unsupervised feature extraction for image classification. Neural Networks.115 (July 2019). 65--71. DOI= https:\/\/doi.org\/10.1016\/j.neunet.2019.03.008"},{"key":"e_1_3_2_1_17_1","first-page":"7","article-title":"Flexible manifold embedding: A framework for semi-supervised and unsupervised dimension reduction","volume":"19","author":"Nie F.","year":"2010","unstructured":"Nie , F. , Xu , D. , Tsang , I. W. H. , & Zhang , C. 2010 . Flexible manifold embedding: A framework for semi-supervised and unsupervised dimension reduction . IEEE Transactions on Image Processing. 19 , 7 (March 2010).1921--1932. DOI= 10.1109\/TIP.2010.2044958 Nie, F., Xu, D., Tsang, I. W. H., & Zhang, C. 2010. Flexible manifold embedding: A framework for semi-supervised and unsupervised dimension reduction. IEEE Transactions on Image Processing. 19, 7 (March 2010).1921--1932. DOI= 10.1109\/TIP.2010.2044958","journal-title":"IEEE Transactions on Image Processing."},{"key":"e_1_3_2_1_18_1","first-page":"2592","volume-title":"Proceedings of Proceedings of the 26th International Joint Conference on Artificial Intelligence","author":"Pang T.","year":"2017","unstructured":"Pang , T. , Nie , F. , & Han , J. ( 2017 , August). Flexible Orthogonal Neighborhood Preserving Embedding . In Proceedings of Proceedings of the 26th International Joint Conference on Artificial Intelligence ( Melbourne, Australia August 19-25, 2017). pp. 2592 -- 2598 . DOI= 10.24963\/ijcai.2017\/361 Pang, T., Nie, F., & Han, J. (2017, August). Flexible Orthogonal Neighborhood Preserving Embedding. In Proceedings of Proceedings of the 26th International Joint Conference on Artificial Intelligence (Melbourne, Australia August 19-25, 2017). pp. 2592--2598. DOI= 10.24963\/ijcai.2017\/361"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44851-9_31"},{"key":"e_1_3_2_1_20_1","volume-title":"Graph construction usingadaptive local hybrid coding scheme. Neural Networks. 95(November","author":"Dornaika F.","year":"2017","unstructured":"Dornaika , F. , Kejani , M. , & Bosaghzadeh , A. 2017. Graph construction usingadaptive local hybrid coding scheme. Neural Networks. 95(November 2017 ).91--101. DOI=10.1016\/j.neunet.2017.08.002 Dornaika, F., Kejani, M., & Bosaghzadeh, A. 2017. Graph construction usingadaptive local hybrid coding scheme. Neural Networks. 95(November 2017).91--101. DOI=10.1016\/j.neunet.2017.08.002"},{"key":"e_1_3_2_1_21_1","volume-title":"Semi-supervised marginal fisher analysis for hyperspectral image classification. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. (September","author":"Huang H.","year":"2012","unstructured":"Huang , H. , Liu , J. , & Pan , Y. 2012. Semi-supervised marginal fisher analysis for hyperspectral image classification. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. (September 2012 , Melbourne, Australia ). Volume I- 3, 2012 DOI= 10.5194\/isprsannals-I-3-377-2012 Huang, H., Liu, J., & Pan, Y. 2012. Semi-supervised marginal fisher analysis for hyperspectral image classification. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. (September 2012, Melbourne, Australia). Volume I-3, 2012 DOI= 10.5194\/isprsannals-I-3-377-2012"},{"key":"e_1_3_2_1_22_1","unstructured":"Kipf T. N. & Welling M. 2016. Semi-supervised classification with graph convolutional networks.arXiv preprint. arXiv:1609.02907. Kipf T. N. & Welling M. 2016. Semi-supervised classification with graph convolutional networks.arXiv preprint. arXiv:1609.02907."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2399456"},{"key":"e_1_3_2_1_24_1","volume-title":"Flexible semi-supervised embedding based on adaptive loss regression: application to image categorization. Information Sciences. 444(May","author":"Traboulsi Y. E.","year":"2018","unstructured":"Traboulsi , Y. E. , & Dornaika , F. 2018. Flexible semi-supervised embedding based on adaptive loss regression: application to image categorization. Information Sciences. 444(May 2018 ). 1--9 DOI= https:\/\/doi.org\/10.1016\/j.ins.2018.02.044 10.1016\/j.ins.2018.02.044 Traboulsi, Y. E., & Dornaika, F. 2018. Flexible semi-supervised embedding based on adaptive loss regression: application to image categorization. Information Sciences. 444(May 2018). 1--9 DOI= https:\/\/doi.org\/10.1016\/j.ins.2018.02.044"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0148655"},{"key":"e_1_3_2_1_26_1","volume-title":"Proceedings of the International Conference on Neural Information Processing Systems","author":"Zhen C.","year":"2014","unstructured":"Zhen , C. , Hong , C. , Shan , S. , & Chen , X. 2014 . Generalized Unsupervised Manifold Alignment . In Proceedings of the International Conference on Neural Information Processing Systems ( Montreal, Canada. December 08-13, 2014). pp:2429--2437. Zhen, C., Hong, C., Shan, S., & Chen, X. 2014. Generalized Unsupervised Manifold Alignment. In Proceedings of the International Conference on Neural Information Processing Systems (Montreal, Canada. December 08-13, 2014). pp:2429--2437."},{"key":"e_1_3_2_1_27_1","first-page":"11","volume-title":"Proceedings of the 22nd International Joint Conference on Artificial Intelligence(Barcelona","author":"Wang C.","year":"2011","unstructured":"Wang , C. ,& Mahadevan , S. 2011 . Heterogeneous Domain Adaptation Using Manifold Alignment . In Proceedings of the 22nd International Joint Conference on Artificial Intelligence(Barcelona , Catalonia, Spain , July 16-22, 2011). 1541--1546. DOI= 10.5591\/978-1-57735-516-8\/IJCAI 11 - 259 Wang, C.,& Mahadevan, S. 2011. Heterogeneous Domain Adaptation Using Manifold Alignment. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence(Barcelona, Catalonia, Spain, July 16-22, 2011). 1541--1546. DOI= 10.5591\/978-1-57735-516-8\/IJCAI11-259"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-010-0189-3"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"e_1_3_2_1_30_1","first-page":"12","article-title":"A new domain adaption algorithm based on weights adaption from the source domain","volume":"13","author":"Nannan L.","year":"2018","unstructured":"Nannan , L. , Fei , C. , Haoran , Q. ,& Shuang , X. 2018 . A new domain adaption algorithm based on weights adaption from the source domain . IEEJ Transactions on Electrical and Electronic Engineering. 13 , 12 (June 2018): 1769--1776. DOI= 10.1002\/tee.22739 Nannan, L., Fei, C., Haoran, Q.,& Shuang, X. 2018. A new domain adaption algorithm based on weights adaption from the source domain. IEEJ Transactions on Electrical and Electronic Engineering. 13, 12 (June 2018): 1769--1776. DOI= 10.1002\/tee.22739","journal-title":"IEEJ Transactions on Electrical and Electronic Engineering."}],"event":{"name":"ICNCC 2019: 2019 The 8th International Conference on Networks, Communication and Computing","acronym":"ICNCC 2019","location":"Luoyang China"},"container-title":["Proceedings of the 2019 8th International Conference on Networks, Communication and Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3375998.3376022","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T20:44:51Z","timestamp":1680813891000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3375998.3376022"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,13]]},"references-count":30,"alternative-id":["10.1145\/3375998.3376022","10.1145\/3375998"],"URL":"https:\/\/doi.org\/10.1145\/3375998.3376022","relation":{},"subject":[],"published":{"date-parts":[[2019,12,13]]},"assertion":[{"value":"2020-01-28","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}