{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T05:12:52Z","timestamp":1748409172025},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tkde.2021.3099294","type":"journal-article","created":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T22:19:44Z","timestamp":1627337984000},"page":"1-1","source":"Crossref","is-referenced-by-count":11,"title":["Label distribution learning by maintaining label ranking relation"],"prefix":"10.1109","author":[{"given":"Xiuyi","family":"Jia","sequence":"first","affiliation":[]},{"given":"Xiaoxia","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Weiwei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yunan","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Jihua","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.4018\/jdwm.2007070101"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2545658"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11664"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/369"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/99"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/364"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/518"},{"key":"ref8","first-page":"897","article-title":"Mcrank: Learning to rank using multiple classification and gradient boosting","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref9","article-title":"Uhigh-level feature detection with forests of fuzzy decision trees combined with the rankboost algorithm","volume-title":"Proc. TRECVID Workshop","author":"Marsala"},{"key":"ref10","first-page":"1883","article-title":"Learning to rank by optimizing NDCG measure","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Valizadegan"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v24i1.7657"},{"key":"ref12","first-page":"4489","article-title":"Logistic boosting regression for label distribution learning","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Chao"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11693"},{"issue":"1","key":"ref14","first-page":"39","article-title":"A maximum entropy approach to natural language processing","volume":"22","author":"Berger","year":"1996","journal-title":"Comput. Linguistics"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01007"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.764"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d16-1061"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.237"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806328"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/460"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/515"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/11776420_44"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/S0306-4573(01)00037-1"},{"key":"ref24","first-page":"897","article-title":"McRank: Learning to rank using multiple classification and gradient boosting","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/775066.775067"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"ref27","first-page":"1697","article-title":"A general boosting method and its application to learning ranking functions for web search","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Zheng"},{"key":"ref28","first-page":"25","article-title":"Learning to rank using an ensemble of Lambda-gradient models","volume-title":"Proc. Int. Conf. Yahoo! Learn. Rank Challenge","author":"Burges"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-88942-5_13"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273513"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-46133-1_15"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372165"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.208"},{"key":"ref34","first-page":"2234","article-title":"Semantic concept discovery for large-scale zero-shot event detection","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Chang"},{"issue":"4","key":"ref35","first-page":"300","article-title":"Comprehensive survey on distance\/similarity measures between probability density functions","volume":"1","author":"Cha","year":"2007","journal-title":"Int. J. Math. Models Methods Appl. Sci."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"ref37","article-title":"On the convergence of Adam and beyond","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Reddi"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/AFGR.1998.670949"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298687"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.95.25.14863"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.478"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2004.03.009"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.2307\/1422689"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/30.1-2.81"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2984622"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11609"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.51"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/4358933\/09495131.pdf?arnumber=9495131","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T23:08:53Z","timestamp":1705014533000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9495131\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/tkde.2021.3099294","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}