{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:27:12Z","timestamp":1730266032948,"version":"3.28.0"},"reference-count":30,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892227","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T15:56:04Z","timestamp":1664553364000},"page":"1-7","source":"Crossref","is-referenced-by-count":0,"title":["Label Distribution Learning Based on Square Root Pearson"],"prefix":"10.1109","author":[{"given":"Chenhao","family":"Fu","sequence":"first","affiliation":[{"name":"School of Computer and Information Engineering, Zhejiang Gongshang University,Hangzhou,China,310018"}]},{"given":"Bailin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Zhejiang Gongshang University,Hangzhou,China,310018"}]},{"given":"Shi","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Zhejiang Gongshang University,Hangzhou,China,310018"}]}],"member":"263","reference":[{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/S0033-5894(03)00088-7"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.4018\/jdwm.2007070101"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.39"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7687-1_910"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.74"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-011-5256-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806328"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1061"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.51"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2013.19"},{"key":"ref19","first-page":"669","article-title":"Multi-label learning by instance differentiation","volume":"7","author":"zhang","year":"2007","journal-title":"AAAI"},{"journal-title":"Dictionary of Distances","year":"2006","author":"deza","key":"ref28"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2943337"},{"journal-title":"Classification Parameter Estimation and State Estimation An Engineering Approach Using MATLAB","year":"2005","author":"van","key":"ref27"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11693"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2943337"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2020.02.003"},{"key":"ref8","first-page":"86","article-title":"Label distri-bution learning by exploiting feature-label correlations locally","author":"li","year":"0","journal-title":"2021 IEEE International Conference on Big Knowledge (ICBK)"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2984622"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11664"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3099294"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2545658"},{"key":"ref20","first-page":"1","article-title":"Comprehensive survey on distance\/similarity measures between probability density functions","volume":"1","author":"cha","year":"2007","journal-title":"city"},{"key":"ref22","first-page":"39","article-title":"A maximum entropy approach to natural language processing","volume":"22","author":"berger","year":"1996","journal-title":"Computational Lin-guistics"},{"key":"ref21","first-page":"708","article-title":"Selection of target function in label distribution learning","volume":"11","author":"quan","year":"2017","journal-title":"Journal of Frontiers of Computer Science and Technology"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.95.25.14863"},{"journal-title":"Numerical Optimization","year":"2006","author":"jorge","key":"ref23"},{"key":"ref26","first-page":"211","article-title":"A 3d facial expression database for facial behavior research","author":"rosato","year":"2006","journal-title":"2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/AFGR.1998.670949"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2022,7,18]]},"location":"Padua, Italy","end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892227.pdf?arnumber=9892227","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T16:52:51Z","timestamp":1665766371000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892227\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892227","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}