{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T17:59:05Z","timestamp":1722016745234},"reference-count":79,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"vor","delay-in-days":264,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["EURO Journal on Computational Optimization"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1016\/j.ejco.2023.100079","type":"journal-article","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T16:32:20Z","timestamp":1696005140000},"page":"100079","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Laplacian-based semi-Supervised learning in multilayer hypergraphs by coordinate descent"],"prefix":"10.1016","volume":"11","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-2653-8533","authenticated-orcid":false,"given":"Sara","family":"Venturini","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9126-3994","authenticated-orcid":false,"given":"Andrea","family":"Cristofari","sequence":"additional","affiliation":[]},{"given":"Francesco","family":"Rinaldi","sequence":"additional","affiliation":[]},{"given":"Francesco","family":"Tudisco","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.ejco.2023.100079_bib0001","article-title":"Combining graph laplacians for semi\u2013supervised learning","volume":"18","author":"Argyriou","year":"2005","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.ejco.2023.100079_bib0002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2020.05.004","article-title":"Networks beyond pairwise interactions: structure and dynamics","volume":"874","author":"Battiston","year":"2020","journal-title":"Phys. Rep."},{"issue":"3","key":"10.1016\/j.ejco.2023.100079_bib0003","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1007\/s10957-013-0491-5","article-title":"The 2-coordinate descent method for solving double-sided simplex constrained minimization problems","volume":"162","author":"Beck","year":"2014","journal-title":"J. Optim. Theory Appl."},{"key":"10.1016\/j.ejco.2023.100079_bib0004","series-title":"Nonlinear Programming","author":"Bertsekas","year":"1999"},{"key":"10.1016\/j.ejco.2023.100079_bib0005","series-title":"Parallel and Distributed Computation: Numerical Methods","author":"Bertsekas","year":"2015"},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10589-022-00389-5","article-title":"Block coordinate descent for smooth nonconvex constrained minimization","volume":"83","author":"Birgin","year":"2022","journal-title":"Comput. Optim. Appl."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0007","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2014.07.001","article-title":"The structure and dynamics of multilayer networks","volume":"544","author":"Boccaletti","year":"2014","journal-title":"Phys. Rep."},{"key":"10.1016\/j.ejco.2023.100079_bib0008","series-title":"Proceedings of the 26th annual international conference on machine learning","first-page":"81","article-title":"Spectral clustering based on the graph p-Laplacian","author":"B\u00fchler","year":"2009"},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0009","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1088\/1361-6544\/aae949","article-title":"The game theoretic p-Laplacian and semi-supervised learning with few labels","volume":"32","author":"Calder","year":"2018","journal-title":"Nonlinearity"},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0010","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.ejor.2013.05.049","article-title":"On the convergence of inexact block coordinate descent methods for constrained optimization","volume":"231","author":"Cassioli","year":"2013","journal-title":"Eur. J. Oper. Res."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0011","first-page":"4","article-title":"Semi-supervised learning. adaptive computation and machine learning","volume":"1","author":"Chapelle","year":"2010","journal-title":"Methods"},{"key":"10.1016\/j.ejco.2023.100079_bib0012","series-title":"International Conference on Machine Learning","first-page":"1172","article-title":"Random walks on hypergraphs with edge-dependent vertex weights","author":"Chitra","year":"2019"},{"issue":"28","key":"10.1016\/j.ejco.2023.100079_bib0013","doi-asserted-by":"crossref","first-page":"eabh1303","DOI":"10.1126\/sciadv.abh1303","article-title":"Generative hypergraph clustering: from blockmodels to modularity","volume":"7","author":"Chodrow","year":"2021","journal-title":"Sci. Adv."},{"issue":"3","key":"10.1016\/j.ejco.2023.100079_bib0014","doi-asserted-by":"crossref","first-page":"1392","DOI":"10.1137\/19M1270446","article-title":"Total variation based community detection using a nonlinear optimization approach","volume":"80","author":"Cristofari","year":"2020","journal-title":"SIAM J. Appl. Math."},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0015","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1007\/s10589-019-00082-0","article-title":"An almost cyclic 2-coordinate descent method for singly linearly constrained problems","volume":"73","author":"Cristofari","year":"2019","journal-title":"Comput. Optim. Appl."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0016","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.ejor.2022.09.030","article-title":"A decomposition method for lasso problems with zero-sum constraint","volume":"306","author":"Cristofari","year":"2023","journal-title":"Eur. J. Oper. Res."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0017","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1137\/141000737","article-title":"A fast active set block coordinate descent algorithm for \u21131-Regularized least squares","volume":"26","author":"De Santis","year":"2016","journal-title":"SIAM J. Optim."},{"key":"10.1016\/j.ejco.2023.100079_bib0018","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.acha.2022.12.003","article-title":"Nodal domain count for the generalized graph p-Laplacian","volume":"64","author":"Deidda","year":"2023","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"10.1016\/j.ejco.2023.100079_bib0019","series-title":"Complementarity: Applications, Algorithms and Extensions","first-page":"121","article-title":"Optimization approaches to semi-supervised learning","author":"Demiriz","year":"2001"},{"key":"10.1016\/j.ejco.2023.100079_bib0020","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/s101070100263","article-title":"Benchmarking optimization software with performance profiles","volume":"91","author":"Dolan","year":"2002","journal-title":"Math. Program."},{"key":"10.1016\/j.ejco.2023.100079_bib0021","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Learning from semi-supervised weak-label data","volume":"volume\u00a032","author":"Dong","year":"2018"},{"key":"10.1016\/j.ejco.2023.100079_bib0022","series-title":"Conference on Learning Theory","first-page":"879","article-title":"Asymptotic behavior of\u2216ell_p-based laplacian regularization in semi-supervised learning","author":"El Alaoui","year":"2016"},{"issue":"5","key":"10.1016\/j.ejco.2023.100079_bib0023","doi-asserted-by":"crossref","first-page":"625","DOI":"10.14778\/3055540.3055554","article-title":"Zoobp: belief propagation for heterogeneous networks","volume":"10","author":"Eswaran","year":"2017","journal-title":"Proc. VLDB Endowment"},{"key":"10.1016\/j.ejco.2023.100079_bib0024","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.acha.2022.01.004","article-title":"Analysis and algorithms for \u2113p-based semi-supervised learning on graphs","volume":"60","author":"Flores","year":"2022","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"10.1016\/j.ejco.2023.100079_bib0025","article-title":"On convergence of a q-random coordinate constrained algorithm for non-convex problems","author":"Ghaffari-Hadigheh","year":"2022","journal-title":"arXiv preprint arXiv:2210.09665"},{"issue":"4","key":"10.1016\/j.ejco.2023.100079_bib0026","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1080\/10556789908805730","article-title":"Globally convergent block-coordinate techniques for unconstrained optimization","volume":"10","author":"Grippo","year":"1999","journal-title":"Optim. Methods Softw."},{"issue":"3","key":"10.1016\/j.ejco.2023.100079_bib0027","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/S0167-6377(99)00074-7","article-title":"On the convergence of the block nonlinear gauss\u2013Seidel method under convex constraints","volume":"26","author":"Grippo","year":"2000","journal-title":"Oper. Res. Lett."},{"key":"10.1016\/j.ejco.2023.100079_bib0028","series-title":"Proceedings of the 2018\u00a0SIAM International Conference on Data Mining","first-page":"702","article-title":"Smacd: semi-supervised multi-aspect community detection","author":"Gujral","year":"2018"},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0029","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s10107-019-01438-4","article-title":"Randomness and permutations in coordinate descent methods","volume":"181","author":"G\u00fcrb\u00fczbalaban","year":"2020","journal-title":"Math. Program."},{"key":"10.1016\/j.ejco.2023.100079_bib0030","article-title":"The total variation on hypergraphs-learning on hypergraphs revisited","volume":"26","author":"Hein","year":"2013","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0031","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/0378-8733(83)90021-7","article-title":"Stochastic blockmodels: first steps","volume":"5","author":"Holland","year":"1983","journal-title":"Soc. Netw."},{"issue":"12","key":"10.1016\/j.ejco.2023.100079_bib0032","doi-asserted-by":"crossref","first-page":"e0243485","DOI":"10.1371\/journal.pone.0243485","article-title":"Local hypergraph clustering using capacity releasing diffusion","volume":"15","author":"Ibrahim","year":"2020","journal-title":"PLoS ONE"},{"issue":"12","key":"10.1016\/j.ejco.2023.100079_bib0033","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1109\/TNNLS.2013.2271327","article-title":"Multiple graph label propagation by sparse integration","volume":"24","author":"Karasuyama","year":"2013","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.ejco.2023.100079_bib0034","series-title":"Joint European conference on machine learning and knowledge discovery in databases","first-page":"795","article-title":"Linear convergence of gradient and proximal-gradient methods under the polyak-\u0142ojasiewicz condition","author":"Karimi","year":"2016"},{"key":"10.1016\/j.ejco.2023.100079_bib0035","series-title":"Conference on Learning Theory","first-page":"1190","article-title":"Algorithms for Lipschitz learning on graphs","author":"Kyng","year":"2015"},{"issue":"6","key":"10.1016\/j.ejco.2023.100079_bib0036","doi-asserted-by":"crossref","first-page":"1288","DOI":"10.1109\/72.963765","article-title":"On the convergence of the decomposition method for support vector machines","volume":"12","author":"Lin","year":"2001","journal-title":"IEEE Trans. Neural Netw."},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0037","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s10589-007-9044-x","article-title":"A convergent decomposition algorithm for support vector machines","volume":"38","author":"Lucidi","year":"2007","journal-title":"Comput. Optim. Appl."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0038","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/BF00939948","article-title":"On the convergence of the coordinate descent method for convex differentiable minimization","volume":"72","author":"Luo","year":"1992","journal-title":"J. Optim. Theory Appl."},{"issue":"3","key":"10.1016\/j.ejco.2023.100079_bib0039","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3444688","article-title":"Community detection in multiplex networks","volume":"54","author":"Magnani","year":"2021","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"10.1016\/j.ejco.2023.100079_bib0040","article-title":"Generalized matrix means for semi-supervised learning with multilayer graphs","author":"Mercado","year":"2019","journal-title":"arXiv:1910.13951"},{"key":"10.1016\/j.ejco.2023.100079_bib0041","first-page":"1330","article-title":"Semi-supervised learning with the graph laplacian: the limit of infinite unlabelled data","volume":"22","author":"Nadler","year":"2009","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0042","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s10589-013-9598-8","article-title":"A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints","volume":"57","author":"Necoara","year":"2014","journal-title":"Comput. Optim. Appl."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0043","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/s10957-016-1058-z","article-title":"Random block coordinate descent methods for linearly constrained optimization over networks","volume":"173","author":"Necoara","year":"2017","journal-title":"J. Optim. Theory Appl."},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0044","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1137\/100802001","article-title":"Efficiency of coordinate descent methods on huge-scale optimization problems","volume":"22","author":"Nesterov","year":"2012","journal-title":"SIAM J. Optim."},{"key":"10.1016\/j.ejco.2023.100079_bib0045","series-title":"IJCAI","first-page":"1881","article-title":"Parameter-free auto-weighted multiple graph learning: a framework for multiview clustering and semi-supervised classification","author":"Nie","year":"2016"},{"key":"10.1016\/j.ejco.2023.100079_sbref0046","series-title":"Advances in Neural Information Processing Systems","article-title":"Learning with local and global consistency","volume":"volume\u00a016","author":"Zhou","year":"2003"},{"key":"10.1016\/j.ejco.2023.100079_bib0047","series-title":"International Conference on Machine Learning","first-page":"1632","article-title":"Coordinate descent converges faster with the Gauss-Southwell rule than random selection","author":"Nutini","year":"2015"},{"issue":"131","key":"10.1016\/j.ejco.2023.100079_bib0048","first-page":"1","article-title":"Let\u2019S make block coordinate descent converge faster: faster greedy rules, message-Passing, active-Set complexity, and superlinear convergence","volume":"23","author":"Nutini","year":"2022","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0049","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s10898-014-0151-9","article-title":"Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization","volume":"61","author":"Patrascu","year":"2015","journal-title":"J. Global Optim."},{"key":"10.1016\/j.ejco.2023.100079_bib0050","series-title":"International Conference on Machine Learning","first-page":"17945","article-title":"Nonlinear Feature Diffusion on Hypergraphs","author":"Prokopchik","year":"2022"},{"issue":"5","key":"10.1016\/j.ejco.2023.100079_bib0051","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1080\/10556788.2016.1190361","article-title":"Coordinate descent with arbitrary sampling II: expected separable overapproximation","volume":"31","author":"Qu","year":"2016","journal-title":"Optim. Method. Softw."},{"issue":"2","key":"10.1016\/j.ejco.2023.100079_bib0052","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1137\/120891009","article-title":"A unified convergence analysis of block successive minimization methods for nonsmooth optimization","volume":"23","author":"Razaviyayn","year":"2013","journal-title":"SIAM J. Optim."},{"key":"10.1016\/j.ejco.2023.100079_bib0053","article-title":"Large-scale randomized-coordinate descent methods with non-separable linear constraints","author":"Reddi","year":"2015","journal-title":"Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI)"},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0054","first-page":"2657","article-title":"Distributed coordinate descent method for learning with big data","volume":"17","author":"Richt\u00e1rik","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.ejco.2023.100079_bib0055","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10107-015-0901-6","article-title":"Parallel coordinate descent methods for big data optimization","volume":"156","author":"Richt\u00e1rik","year":"2016","journal-title":"Math. Program."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0056","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10107-012-0614-z","article-title":"Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function","volume":"144","author":"Richt\u00e1rik","year":"2014","journal-title":"Math. Program."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0057","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1007\/s10107-020-01602-1","article-title":"Parallel random block-coordinate forward\u2013backward algorithm: a unified convergence analysis","volume":"193","author":"Salzo","year":"2022","journal-title":"Math. Program."},{"issue":"6","key":"10.1016\/j.ejco.2023.100079_bib0058","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1007\/BF00934779","article-title":"On the convergence of sequential minimization algorithms","volume":"12","author":"Sargent","year":"1973","journal-title":"J. Optim. Theory Appl."},{"issue":"3","key":"10.1016\/j.ejco.2023.100079_bib0059","doi-asserted-by":"crossref","first-page":"2085","DOI":"10.1137\/17M115222X","article-title":"Analysis of p-Laplacian regularization in semisupervised learning","volume":"51","author":"Slepcev","year":"2019","journal-title":"SIAM J. Math. Anal."},{"key":"10.1016\/j.ejco.2023.100079_bib0060","article-title":"Graph-based semi-supervised learning: acomprehensive review","author":"Song","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"4","key":"10.1016\/j.ejco.2023.100079_bib0061","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-031-01571-7","article-title":"Graph-based semi-supervised learning","volume":"8","author":"Subramanya","year":"2014","journal-title":"Synthesis Lect. Artif. Intell. Mach. Learn."},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0062","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/s10107-007-0170-0","article-title":"A coordinate gradient descent method for nonsmooth separable minimization","volume":"117","author":"Tseng","year":"2009","journal-title":"Math. Program."},{"issue":"3","key":"10.1016\/j.ejco.2023.100079_bib0063","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1007\/s10957-008-9458-3","article-title":"Block-coordinate gradient descent method for linearly constrained nonsmooth separable optimization","volume":"140","author":"Tseng","year":"2009","journal-title":"J. Optim. Theory Appl."},{"issue":"suppl_2","key":"10.1016\/j.ejco.2023.100079_bib0064","doi-asserted-by":"crossref","first-page":"ii59","DOI":"10.1093\/bioinformatics\/bti1110","article-title":"Fast protein classification with multiple networks","volume":"21","author":"Tsuda","year":"2005","journal-title":"Bioinformatics"},{"key":"10.1016\/j.ejco.2023.100079_bib0065","doi-asserted-by":"crossref","first-page":"883","DOI":"10.4171\/JST\/216","article-title":"A nodal domain theorem and a higher-order cheeger inequality for the graph p-laplacian","volume":"8","author":"Tudisco","year":"2018","journal-title":"EMS J. Spectral Theory"},{"key":"10.1016\/j.ejco.2023.100079_bib0066","doi-asserted-by":"crossref","first-page":"2393","DOI":"10.1137\/17M1144143","article-title":"Community detection in networks via nonlinear modularity eigenvectors","volume":"78","author":"Tudisco","year":"2018","journal-title":"SIAM J. Appl. Math."},{"key":"10.1016\/j.ejco.2023.100079_bib0067","series-title":"Proceedings of The Web Conference","first-page":"toappear","article-title":"Nonlinear higher-order label spreading","author":"Tudisco","year":"2021"},{"key":"10.1016\/j.ejco.2023.100079_bib0068","article-title":"Nonlinear spectral duality","author":"Tudisco","year":"2022","journal-title":"arxiv:2209.06241"},{"key":"10.1016\/j.ejco.2023.100079_bib0069","series-title":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"1708","article-title":"Minimizing localized ratio cut objectives in hypergraphs","author":"Veldt","year":"2020"},{"issue":"6","key":"10.1016\/j.ejco.2023.100079_bib0070","doi-asserted-by":"crossref","first-page":"cnac048","DOI":"10.1093\/comnet\/cnac048","article-title":"A variance-aware multiobjective louvain-like method for community detection in multiplex networks","volume":"10","author":"Venturini","year":"2022","journal-title":"J. Complex Netw."},{"key":"10.1016\/j.ejco.2023.100079_bib0071","series-title":"Proceedings of the 40th International Conference on Machine Learning","first-page":"35006","article-title":"Learning the right layers a data-driven layer-aggregation strategy for semi-supervised learning on multilayer graphs","volume":"volume 202","author":"Venturini","year":"2023"},{"issue":"5","key":"10.1016\/j.ejco.2023.100079_bib0072","doi-asserted-by":"crossref","first-page":"698","DOI":"10.14778\/3377369.3377378","article-title":"MEGA: multi-view semi-supervised clustering of hypergraphs","volume":"13","author":"Whang","year":"2020","journal-title":"Proc. VLDB Endowment"},{"issue":"1","key":"10.1016\/j.ejco.2023.100079_bib0073","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10107-015-0892-3","article-title":"Coordinate descent algorithms","volume":"151","author":"Wright","year":"2015","journal-title":"Math. Program."},{"key":"10.1016\/j.ejco.2023.100079_bib0074","series-title":"Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining","first-page":"555","article-title":"Local higher-order graph clustering","author":"Yin","year":"2017"},{"key":"10.1016\/j.ejco.2023.100079_bib0075","series-title":"International Conference on Machine Learning","first-page":"4026","article-title":"Re-revisiting learning on hypergraphs: confidence interval and subgradient method","author":"Zhang","year":"2017"},{"key":"10.1016\/j.ejco.2023.100079_bib0076","article-title":"Learning with hypergraphs: clustering, classification, and embedding","volume":"19","author":"Zhou","year":"2006","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.ejco.2023.100079_bib0077","series-title":"Proceedings of the 24th international conference on Machine learning","first-page":"1159","article-title":"Spectral clustering and transductive learning with multiple views","author":"Zhou","year":"2007"},{"key":"10.1016\/j.ejco.2023.100079_bib0078","series-title":"Proceedings of the fourteenth international conference on artificial intelligence and statistics","first-page":"892","article-title":"Semi-supervised learning by higher order regularization","author":"Zhou","year":"2011"},{"key":"10.1016\/j.ejco.2023.100079_bib0079","series-title":"Proceedings of the 20th International conference on Machine learning (ICML-03)","first-page":"912","article-title":"Semi-supervised learning using gaussian fields and harmonic functions","author":"Zhu","year":"2003"}],"container-title":["EURO Journal on Computational Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2192440623000230?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2192440623000230?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T09:39:49Z","timestamp":1702633189000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2192440623000230"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":79,"alternative-id":["S2192440623000230"],"URL":"https:\/\/doi.org\/10.1016\/j.ejco.2023.100079","relation":{},"ISSN":["2192-4406"],"issn-type":[{"value":"2192-4406","type":"print"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Laplacian-based semi-Supervised learning in multilayer hypergraphs by coordinate descent","name":"articletitle","label":"Article Title"},{"value":"EURO Journal on Computational Optimization","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejco.2023.100079","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 The Author(s). Published by Elsevier B.V. on behalf of Association of European Operational Research Societies (EURO).","name":"copyright","label":"Copyright"}],"article-number":"100079"}}