{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:01:29Z","timestamp":1752192089997,"version":"3.41.2"},"reference-count":69,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01EB026936"],"award-info":[{"award-number":["R01EB026936"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CCF-2217058"],"award-info":[{"award-number":["CCF-2217058"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Signal and Inf. Process. over Networks"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tsipn.2025.3572698","type":"journal-article","created":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T14:06:48Z","timestamp":1748268408000},"page":"641-654","source":"Crossref","is-referenced-by-count":0,"title":["Graph Laplacian Learning With Exponential Family Noise"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7963-991X","authenticated-orcid":false,"given":"Changhao","family":"Shi","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering Department, UC San Diego, La Jolla, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5287-3626","authenticated-orcid":false,"given":"Gal","family":"Mishne","sequence":"additional","affiliation":[{"name":"Hal&imath;c&imath;o&#x011F;lu Data Science Institute, UC San Diego, La Jolla, CA, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2575"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139111"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.socnet.2006.08.002"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-4371(02)01089-0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2018.2820126"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2018.2890143"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2664039"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2018.2804318"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2021.3122522"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0128136"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2602809"},{"key":"ref12","first-page":"920","article-title":"How to learn a graph from smooth signals","volume-title":"Proc. 19th Int. Conf. Artif. Intell. Statist.","author":"Kalofolias","year":"2016"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2017.2726975"},{"issue":"22","key":"ref14","first-page":"1","article-title":"A unified framework for structured graph learning via spectral constraints","volume":"21","author":"Kumar","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref15","doi-asserted-by":"crossref","DOI":"10.1016\/j.jneumeth.2020.108649","article-title":"Examining brain maturation during adolescence using graph laplacian learning based Fourier transform","volume":"338","author":"Wang","year":"2020","journal-title":"J. Neurosci. Methods"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118289"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1089\/cmb.2016.0061"},{"volume-title":"Geometry and Analysis of Dual Networks on Questionnaires","year":"2014","author":"Ankenman","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1037\/abn0000775"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2018.2887284"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2775589"},{"key":"ref22","first-page":"1162","article-title":"Variational inference for sparse network reconstruction from count data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chiquet","year":"2019"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1201\/9780203492024"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.2307\/2528966"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1093\/biostatistics\/kxm045"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1137\/060670985"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1137\/070695915"},{"key":"ref28","first-page":"2101","article-title":"Sparse inverse covariance selection via alternating linearization methods","volume-title":"Proc. 24th Int. Conf. Neural Inf. Process. Syst.","author":"Scheinberg","year":"2010"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s12532-010-0020-6"},{"key":"ref30","first-page":"2330","article-title":"Sparse inverse covariance matrix estimation using quadratic approximation","volume-title":"Proc. 25th Int. Conf. Neural Inf. Process. Syst.","author":"Hsieh","year":"2011"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1198\/jcgs.2011.11051a"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1214\/12-EJS740"},{"key":"ref33","first-page":"755","article-title":"Newton-like methods for sparse inverse covariance estimation","volume-title":"Proc. 26th Int. Conf. Neural Inf. Process. Syst.","author":"Oztoprak","year":"2012"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.2307\/2322600"},{"issue":"1","key":"ref35","first-page":"3813","article-title":"Graphical models via univariate exponential family distributions","volume":"16","author":"Yang","year":"2015","journal-title":"J. Mach. Learn. Res."},{"key":"ref36","first-page":"1302","article-title":"Learning the network structure of heterogeneous data via pairwise exponential Markov random fields","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statisti.","author":"Park","year":"2017"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1004226"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1613\/jair.305"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth448"},{"key":"ref40","article-title":"Large scale graph learning from smooth signals","volume-title":"Proc. 7th Int. Conf. Learn. Repr","author":"Kalofolias","year":"2019"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3123459"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2022.3161079"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2017.2731164"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2017.2731051"},{"key":"ref45","first-page":"1","article-title":"Joint inference of multiple graphs from matrix polynomials","volume":"23","author":"Navarro","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/OJSP.2021.3063926"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2017.2742940"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7953413"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2019.2896229"},{"issue":"1","key":"ref50","first-page":"8766","article-title":"Learning Laplacian matrix from graph signals with sparse spectral representation","volume":"22","author":"Humbert","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.laa.2014.04.020"},{"key":"ref52","first-page":"1358","article-title":"Graphical models via generalized linear models","volume-title":"Proc. 26th Int. Conf. Neural Inf. Process. Syst.","author":"Yang","year":"2012"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/76.4.643"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.2307\/2335470"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2916567"},{"key":"ref56","first-page":"778","article-title":"Discovering structure by learning sparse graphs","volume-title":"Proc. 32nd Annu. Conf. Cogn. Sci. Soc.","author":"Lake","year":"2010"},{"article-title":"GSPBOX: A toolbox for signal processing on graphs","year":"2014","author":"Perraudin","key":"ref57"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2010.04.005"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972832.18"},{"article-title":"City of ChicagoData Portal. (nd). retrieved april 25, 2017","year":"2017","author":"Sensors","key":"ref60"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0802631105"},{"key":"ref62","first-page":"485","article-title":"Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data","volume":"9","author":"Banerjee","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref63","article-title":"Neural latents benchmark21: Evaluating latent variable models of neural population activity","volume-title":"Proc. 35th Int. Conf. Neural Inf. Process. Syst. Track on Datasets and Benchmarks","author":"Pei","year":"2021"},{"key":"ref64","first-page":"1350","article-title":"Empirical models of spiking in neural populations","volume-title":"Proc. 25th Int. Conf. Neural Inf. Process. Syst.","author":"Macke","year":"2011"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-53708-y"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.03.011"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5635-7"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2020.2983139"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.3013555"}],"container-title":["IEEE Transactions on Signal and Information Processing over Networks"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6884276\/10789318\/11015258-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6884276\/10789318\/11015258.pdf?arnumber=11015258","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T23:20:52Z","timestamp":1752103252000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11015258\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":69,"URL":"https:\/\/doi.org\/10.1109\/tsipn.2025.3572698","relation":{},"ISSN":["2373-776X","2373-7778"],"issn-type":[{"type":"electronic","value":"2373-776X"},{"type":"electronic","value":"2373-7778"}],"subject":[],"published":{"date-parts":[[2025]]}}}