{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T08:07:33Z","timestamp":1771488453513,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2017,10,23]],"date-time":"2017-10-23T00:00:00Z","timestamp":1508716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Chinese National Natural Science Foundation","award":["61471049"],"award-info":[{"award-number":["61471049"]}]},{"name":"Chinese National Natural Science Foundation","award":["61532018"],"award-info":[{"award-number":["61532018"]}]},{"name":"Chinese National Natural Science Foundation","award":["61372169"],"award-info":[{"award-number":["61372169"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,10,23]]},"DOI":"10.1145\/3126686.3126726","type":"proceedings-article","created":{"date-parts":[[2017,10,23]],"date-time":"2017-10-23T19:20:32Z","timestamp":1508786432000},"page":"332-339","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Towards Improving Canonical Correlation Analysis for Cross-modal Retrieval"],"prefix":"10.1145","author":[{"given":"Jie","family":"Shao","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhicheng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications &amp; Beijing Key Laboratory of Network System and Network Culture, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Su","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications &amp; Beijing Key Laboratory of Network System and Network Culture, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Yue","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,10,23]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of the 30th International Conference on Machine Learning. 1247--1255","author":"Andrew Galen","year":"2013","unstructured":"Galen Andrew , Raman Arora , Jeff Bilmes , and Karen Livescu . 2013 . Deep canonical correlation analysis . In Proceedings of the 30th International Conference on Machine Learning. 1247--1255 . Galen Andrew, Raman Arora, Jeff Bilmes, and Karen Livescu. 2013. Deep canonical correlation analysis. In Proceedings of the 30th International Conference on Machine Learning. 1247--1255."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"e_1_3_2_1_3_1","unstructured":"J. F. Bonnans J. C. Gilbert and Claude Lemarechal. 2006. Numerical optimization: Springer 31--45 pages.  J. F. Bonnans J. C. Gilbert and Claude Lemarechal. 2006. Numerical optimization: Springer 31--45 pages."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1646396.1646452"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/1888089.1888092"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654902"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2808205"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0658-4"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.70791"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967216"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"e_1_3_2_1_12_1","unstructured":"Geoffrey E Hinton and Ruslan Salakhutdinov. 2009. Replicated softmax: an undirected topic model. In Advances in neural information processing systems. 1607--1614.   Geoffrey E Hinton and Ruslan Salakhutdinov. 2009. Replicated softmax: an undirected topic model. In Advances in neural information processing systems. 1607--1614."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.65"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Andrej Karpathy and Li Fei-Fei. 2015. Deep visual-semantic alignments for generating image descriptions Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3128--3137.  Andrej Karpathy and Li Fei-Fei. 2015. Deep visual-semantic alignments for generating image descriptions Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3128--3137.","DOI":"10.1109\/CVPR.2015.7298932"},{"key":"e_1_3_2_1_15_1","volume-title":"2012 IEEE Conference on. IEEE, 2288--2295","author":"Koestinger Martin","year":"2012","unstructured":"Martin Koestinger , Martin Hirzer , Paul Wohlhart , Peter M Roth , and Horst Bischof . 2012 . Large scale metric learning from equivalence constraints Computer Vision and Pattern Recognition (CVPR) , 2012 IEEE Conference on. IEEE, 2288--2295 . Martin Koestinger, Martin Hirzer, Paul Wohlhart, Peter M Roth, and Horst Bischof. 2012. Large scale metric learning from equivalence constraints Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2288--2295."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2014.2387847"},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the 28th International Conference on Machine Learning (ICML-11)","author":"Ngiam Jiquan","year":"2011","unstructured":"Jiquan Ngiam , Aditya Khosla , Mingyu Kim , Juhan Nam , Honglak Lee , and Andrew Y Ng . 2011 . Multimodal deep learning . In Proceedings of the 28th International Conference on Machine Learning (ICML-11) . 689--696. Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, and Andrew Y Ng. 2011. Multimodal deep learning. In Proceedings of the 28th International Conference on Machine Learning (ICML-11). 689--696."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.142"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1873951.1873987"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.06.047"},{"key":"e_1_3_2_1_21_1","unstructured":"Nitish Srivastava and Ruslan Salakhutdinov. 2012. Learning representations for multimodal data with deep belief nets International Conference on Machine Learning Workshop.  Nitish Srivastava and Ruslan Salakhutdinov. 2012. Learning representations for multimodal data with deep belief nets International Conference on Machine Learning Workshop."},{"key":"e_1_3_2_1_22_1","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton . 2008 . Visualizing data using t-SNE . Journal of Machine Learning Research Vol. 9 , 2579 -- 2605 (2008), 85. Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of Machine Learning Research Vol. 9, 2579--2605 (2008), 85.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.06.064"},{"key":"e_1_3_2_1_25_1","first-page":"449","article-title":"Cross-Modal Retrieval With CNN Visual Features: A New Baseline","volume":"47","author":"Wei Y.","year":"2016","unstructured":"Y. Wei , Y. Zhao , C. Lu , and S. Wei . 2016 . Cross-Modal Retrieval With CNN Visual Features: A New Baseline . IEEE Transactions on Cybernetics Vol. 47 , 2 (2016), 449 . Y. Wei, Y. Zhao, C. Lu, and S. Wei. 2016. Cross-Modal Retrieval With CNN Visual Features: A New Baseline. IEEE Transactions on Cybernetics Vol. 47, 2 (2016), 449.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"e_1_3_2_1_26_1","volume-title":"Saul","author":"Weinberger Kilian Q.","year":"2005","unstructured":"Kilian Q. Weinberger , John Blitzer , and Lawrence K . Saul . 2005 . Distance metric learning for large margin nearest neighbor classification Advances in neural information processing systems. 1473--1480. Kilian Q. Weinberger, John Blitzer, and Lawrence K. Saul. 2005. Distance metric learning for large margin nearest neighbor classification Advances in neural information processing systems. 1473--1480."},{"key":"e_1_3_2_1_27_1","volume-title":"Hinton","author":"Welling Max","year":"2004","unstructured":"Max Welling , Michal Rosen-Zvi , and Geoffrey E . Hinton . 2004 . Exponential family harmoniums with an application to information retrieval Advances in neural information processing systems. 1481--1488. Max Welling, Michal Rosen-Zvi, and Geoffrey E. Hinton. 2004. Exponential family harmoniums with an application to information retrieval Advances in neural information processing systems. 1481--1488."},{"key":"e_1_3_2_1_28_1","volume-title":"Large Scale Similarity Learning Using Similar Pairs for Person Verification Thirtieth AAAI Conference on Artificial Intelligence.","author":"Yang Yang","unstructured":"Yang Yang , Shengcai Liao , Zhen Lei , and Stan Z. Li . 2016 . Large Scale Similarity Learning Using Similar Pairs for Person Verification Thirtieth AAAI Conference on Artificial Intelligence. Yang Yang, Shengcai Liao, Zhen Lei, and Stan Z. Li. 2016. Large Scale Similarity Learning Using Similar Pairs for Person Verification Thirtieth AAAI Conference on Artificial Intelligence."}],"event":{"name":"MM '17: ACM Multimedia Conference","location":"Mountain View California USA","acronym":"MM '17","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the on Thematic Workshops of ACM Multimedia 2017"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3126686.3126726","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3126686.3126726","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:10:54Z","timestamp":1750212654000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3126686.3126726"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,23]]},"references-count":28,"alternative-id":["10.1145\/3126686.3126726","10.1145\/3126686"],"URL":"https:\/\/doi.org\/10.1145\/3126686.3126726","relation":{},"subject":[],"published":{"date-parts":[[2017,10,23]]},"assertion":[{"value":"2017-10-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}