{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T07:07:29Z","timestamp":1776064049493,"version":"3.50.1"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"European Union under the Italian National Recovery and Resilience Plan (NRRP) of NextGenerationEU","award":["PE00000001 - program \u201cRESTART\u201d"],"award-info":[{"award-number":["PE00000001 - program \u201cRESTART\u201d"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tsp.2024.3401072","type":"journal-article","created":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T17:38:22Z","timestamp":1715881102000},"page":"2953-2969","source":"Crossref","is-referenced-by-count":1,"title":["Learning Multi-Frequency Partial Correlation Graphs"],"prefix":"10.1109","volume":"72","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6233-4060","authenticated-orcid":false,"given":"Gabriele","family":"D\u2019Acunto","sequence":"first","affiliation":[{"name":"Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4130-3177","authenticated-orcid":false,"given":"Paolo","family":"Di Lorenzo","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Electronics, and Telecommunications, Sapienza University of Rome, Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9464-8315","authenticated-orcid":false,"given":"Francesco","family":"Bonchi","sequence":"additional","affiliation":[{"name":"Centai Institute, Turin, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4749-2933","authenticated-orcid":false,"given":"Stefania","family":"Sardellitti","sequence":"additional","affiliation":[{"name":"Faculty of Engineering in Computer Science, Universitas Mercatorum, University of Italian Chambers of Commerce, Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9846-8741","authenticated-orcid":false,"given":"Sergio","family":"Barbarossa","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Electronics, and Telecommunications, Sapienza University of Rome, Rome, Italy"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2307\/2975974.JSTOR2975974"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2575"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1098\/rstb.2005.1645"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.4636-06.2007"},{"key":"ref5","first-page":"889","article-title":"Detrended partial cross correlation for brain connectivity analysis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Ide","year":"2017"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.05.062"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.03.047"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2018.02.029"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10827-010-0236-5"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1175\/2010jcli3727.1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2009.04.007"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1017\/cbo9780511804458.004"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1201\/b18706"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.14676"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s001840000055"},{"issue":"15","key":"ref16","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":"ref17","first-page":"559","article-title":"On sparse nonparametric conditional covariance selection","volume-title":"Proc. 27th Int. Conf. Mach. Learn., (ICML\u201910)","author":"Kolar","year":"2010"},{"key":"ref18","first-page":"667","article-title":"Optimization methods for sparse pseudo-likelihood graphical model selection","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Oh","year":"2014"},{"key":"ref19","first-page":"440","article-title":"Learning to discover sparse graphical models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Belilovsky","year":"2017"},{"issue":"203","key":"ref20","first-page":"1","article-title":"Learning partial correlation graphs and graphical models by covariance queries.\u201d","volume":"22","author":"Lugosi","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOAS396"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1214\/14-EJS977"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2582464"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2008.09.009"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1214\/19-EJS1621"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm10155"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2015.2425434"},{"key":"ref28","article-title":"Sparse plus low-rank graphical models of time series for functional connectivity in MEG","volume-title":"Proc. 2nd KDD Workshop Mining Learn. Time Ser.","author":"Foti","year":"2016"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2022.107557"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2022.108539"},{"key":"ref31","article-title":"Regularized estimation of sparse spectral precision matrices","author":"Deb","year":"2024"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1953.tb00131.x"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1957.tb00242.x"},{"key":"ref34","article-title":"Frequency domain statistical inference for high-dimensional time series","author":"Krampe","year":"2024"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2010.2040894"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-97142-1_3"},{"key":"ref37","article-title":"JAX: Composable transformations of Python+NumPy programs","author":"Bradbury","year":"2018"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2019.2896229"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2637317"},{"key":"ref40","first-page":"1440","article-title":"Parallel successive convex approximation for nonsmooth nonconvex optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Razaviyayn","year":"2014"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1002\/0471439002"},{"key":"ref42","article-title":"CVX: Matlab software for disciplined convex programming, version 2.1","author":"Grant","year":"2014"},{"issue":"1","key":"ref43","first-page":"2909","article-title":"CVXPY: A python-embedded modeling language for convex optimization","volume":"17","author":"Diamond","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1561\/2400000003"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"ref47","volume-title":"Numerical Analysis","author":"Burden","year":"2015"},{"key":"ref48","article-title":"Learning multiscale non-stationary causal structures","author":"D\u2019Acunto","year":"2023","journal-title":"Trans. Mach. Learn. Res."},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511803161"},{"key":"ref50","article-title":"Large spectral density matrix estimation by thresholding","author":"Sun","year":"2018"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/88.4.1186"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.resourpol.2021.102392"},{"key":"ref53","article-title":"Gas","year":"2020"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/0005-1098(89)90002-2"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24853-0"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2018.01.004"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0493(1981)109<0784:TITGHF>2.0.CO;2"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1063\/1.4978548"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosres.2014.12.012"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.catena.2020.104474"},{"key":"ref61","first-page":"89","article-title":"Long-range dependence and global warming","volume-title":"in Proc. Appl. Statist. Model. Earths Climate Syst.","author":"Smith","year":"1993"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/s00382-005-0106-4"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.adf7202"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0135058100"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2003.09.056"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2019.00545"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4135"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/78\/10347386\/10531218.pdf?arnumber=10531218","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,6]],"date-time":"2024-07-06T04:46:34Z","timestamp":1720241194000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10531218\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":67,"URL":"https:\/\/doi.org\/10.1109\/tsp.2024.3401072","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"value":"1053-587X","type":"print"},{"value":"1941-0476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}