{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T20:07:17Z","timestamp":1761854837346,"version":"build-2065373602"},"reference-count":31,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1109\/icassp.2018.8461603","type":"proceedings-article","created":{"date-parts":[[2018,9,21]],"date-time":"2018-09-21T22:24:48Z","timestamp":1537568688000},"page":"6309-6313","source":"Crossref","is-referenced-by-count":6,"title":["Graph Learning Based on Total Variation Minimization"],"prefix":"10.1109","author":[{"given":"Peter","family":"Berger","sequence":"first","affiliation":[]},{"given":"Manfred","family":"Buchacher","sequence":"additional","affiliation":[]},{"given":"Gabor","family":"Hannak","sequence":"additional","affiliation":[]},{"given":"Gerald","family":"Matz","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2015.1114491"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2014.2354892"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2017.2726978"},{"journal-title":"Graph learning from data under structural and Laplacian constraints","year":"2016","author":"egilmez","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.laa.2014.04.020"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472899"},{"key":"ref14","first-page":"778","article-title":"Discovering structure by learning sparse graph","author":"lake","year":"2010","journal-title":"Proceedings of the 32rd Annual Cognitive Science Conference"},{"key":"ref15","first-page":"6508","article-title":"Learning sparse graphs under smoothness prior","author":"chepuri","year":"2017","journal-title":"ICASSP"},{"key":"ref16","first-page":"920","article-title":"How to learn a graph from smooth signals","author":"kalofolias","year":"2016","journal-title":"Proc Int Conf on Artificial Intelligence and Statistics volume 51 of Proceedings of Machine Learning Research"},{"journal-title":"Large scale graph learning from smooth signals","year":"2017","author":"kalofolias","key":"ref17"},{"key":"ref18","first-page":"161","article-title":"A connectedness constraint for learning sparse graphs","author":"sundin","year":"2017","journal-title":"European Signal Processing Conference EUSIPCO"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2602809"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1002\/0471200611"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781316162750"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2013.2238935"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1126\/science.1215842","article-title":"Identifying influential and susceptible members of social networks","volume":"337","author":"aral","year":"2012","journal-title":"Science"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.92.218701"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-11-175"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/DNSR.2004.1344743"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2329213"},{"key":"ref9","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-20192-9","author":"b\u00fchlmann","year":"2011","journal-title":"Statistics for High-Dimensional Data"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2235192"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2017.2731051"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/GlobalSIP.2016.7905863"},{"key":"ref21","first-page":"1","article-title":"Characterization and inference of graph diffusion processes from observations of stationary signals","author":"pasdeloup","year":"2017","journal-title":"IEEE Trans Signal Inf Process Over Netw"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/TKDE.2007.190672","article-title":"Label propagation through linear neighborhoods","volume":"20","author":"wang","year":"2008","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1145\/1553374.1553432","article-title":"Graph construction and b-matching for semi-supervised learning","author":"jebara","year":"2009","journal-title":"Proceedings of the 26th Annual International Conference on Machine Learning"},{"key":"ref26","first-page":"395","article-title":"Graph adjacency matrix learning for irregularly sampled markovian natural images","author":"colonnese","year":"2017","journal-title":"European Signal Processing Conference EUSIPCO"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553400"}],"event":{"name":"ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2018,4,15]]},"location":"Calgary, AB","end":{"date-parts":[[2018,4,20]]}},"container-title":["2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8450881\/8461260\/08461603.pdf?arnumber=8461603","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T18:19:17Z","timestamp":1751998757000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8461603\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/icassp.2018.8461603","relation":{},"subject":[],"published":{"date-parts":[[2018,4]]}}}