{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T15:48:04Z","timestamp":1743004084769,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030747169"},{"type":"electronic","value":"9783030747176"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-74717-6_10","type":"book-chapter","created":{"date-parts":[[2021,4,16]],"date-time":"2021-04-16T18:04:41Z","timestamp":1618596281000},"page":"87-96","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["HOOD: High-Order Orthogonal Decomposition for Tensors"],"prefix":"10.1007","author":[{"given":"Weitao","family":"Tang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huyunting","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyang","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tonglin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baijian","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,17]]},"reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"Baskaran, M., et al.: Memory-efficient parallel tensor decompositions. In: 2017 IEEE High Performance Extreme Computing Conference (HPEC), pp. 1\u20137. IEEE (2017)","DOI":"10.1109\/HPEC.2017.8091026"},{"issue":"3","key":"10_CR2","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/BF02310791","volume":"35","author":"JD Carroll","year":"1970","unstructured":"Carroll, J.D., Chang, J.J.: Analysis of individual differences in multidimensional scaling via an n-way generalization of \u201ceckart-young\u201d decomposition. Psychometrika 35(3), 283\u2013319 (1970)","journal-title":"Psychometrika"},{"issue":"3","key":"10_CR3","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1109\/MCOM.2018.1700274","volume":"56","author":"M Chen","year":"2018","unstructured":"Chen, M., Zhang, Y., Qiu, M., Guizani, N., Hao, Y.: Spha: smart personal health advisor based on deep analytics. IEEE Commun. Mag. 56(3), 164\u2013169 (2018)","journal-title":"IEEE Commun. Mag."},{"key":"10_CR4","unstructured":"Cho, S., Jun, T.J., Kang, M.: Applying tensor decomposition to image for robustness against adversarial attack. arXiv preprint arXiv:2002.12913 (2020)"},{"issue":"3","key":"10_CR5","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1109\/TBDATA.2016.2597149","volume":"4","author":"W Dai","year":"2016","unstructured":"Dai, W., Qiu, L., Wu, A., Qiu, M.: Cloud infrastructure resource allocation for big data applications. IEEE Trans. Big Data 4(3), 313\u2013324 (2016)","journal-title":"IEEE Trans. Big Data"},{"issue":"4","key":"10_CR6","doi-asserted-by":"publisher","first-page":"1253","DOI":"10.1137\/S0895479896305696","volume":"21","author":"L De Lathauwer","year":"2000","unstructured":"De Lathauwer, L., De Moor, B., Vandewalle, J.: A multilinear singular value decomposition. SIAM J. Matrix Anal. Appl. 21(4), 1253\u20131278 (2000)","journal-title":"SIAM J. Matrix Anal. Appl."},{"issue":"2\u20133","key":"10_CR7","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1016\/j.laa.2006.08.023","volume":"420","author":"P Drineas","year":"2007","unstructured":"Drineas, P., Mahoney, M.W.: A randomized algorithm for a tensor-based generalization of the singular value decomposition. Linear Algebra Appl. 420(2\u20133), 553\u2013571 (2007)","journal-title":"Linear Algebra Appl."},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Huang, H., Liu, X., Zhang, T., Yang, B.: Regression PCA for moving objects separation. In: The 2020 IEEE Global Communications Conference (GLOBECOM 2020), Accepted. IEEE (2020)","DOI":"10.1109\/GLOBECOM42002.2020.9322471"},{"key":"10_CR9","unstructured":"Imaizumi, M., Hayashi, K.: Tensor decomposition with smoothness. In: Proceedings of the 34th International Conference on Machine Learning, vol. 70, pp. 1597\u20131606, JMLR. org (2017)"},{"issue":"1","key":"10_CR10","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1137\/S0895479800368354","volume":"23","author":"TG Kolda","year":"2001","unstructured":"Kolda, T.G.: Orthogonal tensor decompositions. SIAM J. Matrix Anal. Appl. 23(1), 243\u2013255 (2001)","journal-title":"SIAM J. Matrix Anal. Appl."},{"issue":"3","key":"10_CR11","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda, T.G., Bader, B.W.: Tensor decompositions and applications. SIAM Rev. 51(3), 455\u2013500 (2009)","journal-title":"SIAM Rev."},{"key":"10_CR12","doi-asserted-by":"crossref","unstructured":"Kolda, T.G., Sun, J.: Scalable tensor decompositions for multi-aspect data mining. In: Eighth IEEE International Conference on Data Mining, pp. 363\u2013372 (2008)","DOI":"10.1109\/ICDM.2008.89"},{"key":"10_CR13","doi-asserted-by":"crossref","unstructured":"Liu, X., Huang, H., Tang, W., Zhang, T., Yang, B.: Low-rank sparse tensor approximations for large high-resolution videos. In: 19th IEEE International Conference on Machine Learning and Applications (ICMLA 2020), Accepted. IEEE (2020)","DOI":"10.1109\/ICMLA51294.2020.00020"},{"key":"10_CR14","unstructured":"Malik, O.A., Becker, S.: Low-rank tucker decomposition of large tensors using tensorsketch. In: Advances in Neural Information Processing Systems, pp. 10096\u201310106 (2018)"},{"issue":"5","key":"10_CR15","doi-asserted-by":"publisher","first-page":"2295","DOI":"10.1137\/090752286","volume":"33","author":"IV Oseledets","year":"2011","unstructured":"Oseledets, I.V.: Tensor-train decomposition. SIAM J. Sci. Comput. 33(5), 2295\u20132317 (2011)","journal-title":"SIAM J. Sci. Comput."},{"key":"10_CR16","unstructured":"Tang, X., Bi, X., Qu, A.: Individualized multilayer tensor learning with an application in imaging analysis. J. Am. Stat. Assoc. pp. 1\u201326 (2019)"},{"issue":"3","key":"10_CR17","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/BF02289464","volume":"31","author":"LR Tucker","year":"1966","unstructured":"Tucker, L.R.: Some mathematical notes on three-mode factor analysis. Psychometrika 31(3), 279\u2013311 (1966)","journal-title":"Psychometrika"},{"key":"10_CR18","unstructured":"Wang, Y., Tung, H.Y., Smola, A.J., Anandkumar, A.: Fast and guaranteed tensor decomposition via sketching. In: Advances in Neural Information Processing Systems, pp. 991\u2013999 (2015)"},{"key":"10_CR19","doi-asserted-by":"crossref","unstructured":"Zhang, T.: CP decomposition and weighted clique problem. Stat. Probab. Lett. 161, 108723 (2020)","DOI":"10.1016\/j.spl.2020.108723"}],"container-title":["Lecture Notes in Computer Science","Smart Computing and Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-74717-6_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:10:49Z","timestamp":1710267049000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-74717-6_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030747169","9783030747176"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-74717-6_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"17 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SmartCom","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Smart Computing and Communication","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Paris","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"smartc2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.cloud-conf.net\/smartcom\/2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair, OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"162","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"10","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}