{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T11:26:26Z","timestamp":1764588386028},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T00:00:00Z","timestamp":1678665600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T00:00:00Z","timestamp":1678665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Beijing Natural Science Foundation","award":["Z190002"],"award-info":[{"award-number":["Z190002"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Comput Optim Appl"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s10589-023-00465-4","type":"journal-article","created":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T14:03:39Z","timestamp":1678716219000},"page":"1275-1298","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimality conditions for Tucker low-rank tensor optimization"],"prefix":"10.1007","volume":"86","author":[{"given":"Ziyan","family":"Luo","sequence":"first","affiliation":[]},{"given":"Liqun","family":"Qi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,13]]},"reference":[{"key":"465_CR1","doi-asserted-by":"crossref","DOI":"10.1515\/9781400830244","volume-title":"Optimization Algorithms on Matrix Manifolds","author":"PA Absil","year":"2008","unstructured":"Absil, P.A., Mahony, R., Sepulchre, R.: Optimization Algorithms on Matrix Manifolds. Princeton University Press, Princeton (2008)"},{"issue":"1","key":"465_CR2","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1146\/annurev-statistics-042720-020816","volume":"8","author":"X Bi","year":"2021","unstructured":"Bi, X., Tang, X., Yuan, Y., Zhang, Y., Annie, Q.: Tensors in statistics. Annu. Rev. Stat. Appl. 8(1), 345\u2013368 (2021)","journal-title":"Annu. Rev. Stat. Appl."},{"issue":"6","key":"465_CR3","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1007\/s10208-009-9045-5","volume":"9","author":"EJ Cand\u00e8s","year":"2009","unstructured":"Cand\u00e8s, E.J., Recht, B.: Exact matrix completion via convex optimization. Found. Comput. Math. 9(6), 717\u2013772 (2009)","journal-title":"Found. Comput. Math."},{"issue":"12","key":"465_CR4","doi-asserted-by":"crossref","first-page":"4203","DOI":"10.1109\/TIT.2005.858979","volume":"51","author":"EJ Cand\u00e8s","year":"2005","unstructured":"Cand\u00e8s, E.J., Tao, T.: Decoding by linear programming. IEEE Trans. Inf. Theory 51(12), 4203\u20134215 (2005)","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"4","key":"465_CR5","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1109\/TPAMI.2019.2891760","volume":"42","author":"L Canyi","year":"2020","unstructured":"Canyi, L., Feng, J., Chen, Y., Liu, W., Lin, Z., Yan, S.: Tensor robust principal component analysis with a new tensor nuclear norm. IEEE Trans. Pattern Anal. Mach. Intell. 42(4), 925\u2013938 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"465_CR6","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1137\/19M1237016","volume":"41","author":"M Che","year":"2020","unstructured":"Che, M., Wei, Y., Yan, H.: The computation of low multilinear rank approximations of tensors via power scheme and random projection. SIAM J. Matrix Anal. Appl. 41(2), 605\u2013636 (2020)","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"465_CR7","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1007\/s10589-020-00177-z","volume":"75","author":"B Chen","year":"2020","unstructured":"Chen, B., Li, Z.: On tensor spectral $$p$$-norm and its dual norm via partitions. Comput. Optim. Appl. 75, 609\u2013628 (2020)","journal-title":"Comput. Optim. Appl."},{"key":"465_CR8","volume":"122","author":"C Chen","year":"2022","unstructured":"Chen, C., Batselier, K., Wenjian, Yu., Wong, N.: Kernelized support tensor train machines. Pattern Recogn. 122, 108337 (2022)","journal-title":"Pattern Recogn."},{"key":"465_CR9","first-page":"172","volume":"20","author":"H Chen","year":"2019","unstructured":"Chen, H., Raskutti, G., Yuan, M.: Non-convex projected gradient descent for generalized low-rank tensor regression. J. Mach. Learn. Res. 20, 172\u2013208 (2019)","journal-title":"J. Mach. Learn. Res."},{"key":"465_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s10898-021-01124-w","author":"X Chen","year":"2022","unstructured":"Chen, X., Pan, L., Xiu, N.: Solution sets of three sparse optimization problems for multivariate regression. J. Global Optim. (2022). https:\/\/doi.org\/10.1007\/s10898-021-01124-w","journal-title":"J. Global Optim."},{"issue":"5","key":"465_CR11","doi-asserted-by":"crossref","first-page":"2399","DOI":"10.1109\/TIP.2018.2877937","volume":"28","author":"M Cheng","year":"2019","unstructured":"Cheng, M., Jing, L., Michael, K.N.: Tensor-based low-dimensional representation learning for multi-view clustering. IEEE Trans. Image Process. 28(5), 2399\u20132414 (2019)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"465_CR12","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1137\/S0895479896305696","volume":"21","author":"L De Lathauwer","year":"2000","unstructured":"De Lathauwer, L., De Moor, B., Vandewalle, J.: A multilinear singular value decomposition. SIAM J. Matrix Anal. Appl. 21(4), 1253\u20131278 (2000)","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"465_CR13","doi-asserted-by":"crossref","unstructured":"De\u00a0Lathauwer, L., De\u00a0Moor, B., Vandewalle, J..: On the best rank-1 and rank-$$(r_1, r_2,..., r_n)$$ approximation of higher-order tensors. SIAM J. Matrix Anal. Appl. 21, 1324\u20131342 (2000)","DOI":"10.1137\/S0895479898346995"},{"key":"465_CR14","volume-title":"Theory and Computation of Tensors: Multi-Dimensional Arrays","author":"W Ding","year":"2016","unstructured":"Ding, W., Wei, Y.: Theory and Computation of Tensors: Multi-Dimensional Arrays. Elsevier, New York (2016)"},{"issue":"4","key":"465_CR15","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52(4), 1289\u20131306 (2006)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"465_CR16","doi-asserted-by":"crossref","unstructured":"Drakopoulos, G., Spyrou, E., Mylonas, P.: Tensor clustering: a review. In: 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP), pp. 1\u20136 (2019)","DOI":"10.1109\/SMAP.2019.8864898"},{"issue":"4","key":"465_CR17","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1137\/110823298","volume":"32","author":"L Eld\u00e9n","year":"2011","unstructured":"Eld\u00e9n, L., Savas, B.: Perturbation theory and optimality conditions for the best multilinear rank approximation of a tensor. SIAM J. Matrix Anal. Appl. 32(4), 1422\u20131450 (2011)","journal-title":"SIAM J. Matrix Anal. Appl."},{"issue":"1","key":"465_CR18","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1137\/130905010","volume":"35","author":"D Goldfarb","year":"2014","unstructured":"Goldfarb, D., Qin, Z.: Robust low-rank tensor recovery: models and algorithms. SIAM J. Matrix Anal. Appl. 35(1), 225\u2013253 (2014)","journal-title":"SIAM J. Matrix Anal. Appl."},{"issue":"9","key":"465_CR19","doi-asserted-by":"crossref","first-page":"5927","DOI":"10.1109\/TIT.2020.2982499","volume":"66","author":"B Hao","year":"2020","unstructured":"Hao, B., Zhang, A., Cheng, G.: Sparse and low-rank tensor estimation via cubic sketchings. IEEE Trans. Inf. Theory 66(9), 5927\u20135964 (2020)","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"2","key":"465_CR20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0024-3795(93)00070-G","volume":"215","author":"U Helmke","year":"1995","unstructured":"Helmke, U., Shayman, M.A.: Critical points of matrix least squares distance functions. Linear Algebra Appl. 215(2), 1\u201319 (1995)","journal-title":"Linear Algebra Appl."},{"issue":"2","key":"465_CR21","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1007\/s40305-020-00295-9","volume":"8","author":"H Jiang","year":"2020","unstructured":"Jiang, H., Liu, X., Wen, Z., Yuan, Y.: A brief introduction to manifold optimization. J. Oper. Res. Soc. China 8(2), 199\u2013248 (2020)","journal-title":"J. Oper. Res. Soc. China"},{"key":"465_CR22","doi-asserted-by":"crossref","unstructured":"Janzamin, M., Ge, R., Kossaifi, J., Anandkumar, A.: Spectral learning on matrices and tensors. Found. Trends\u00ae Mach. Learn. 12, 393\u2013536 (2019)","DOI":"10.1561\/2200000057"},{"issue":"3","key":"465_CR23","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.laa.2010.09.020","volume":"435","author":"ME Kilmer","year":"2011","unstructured":"Kilmer, M.E., Martin, C.D.: Factorization strategies for third-order tensors. Linear Algebra Appl. 435(3), 641\u2013658 (2011)","journal-title":"Linear Algebra Appl."},{"issue":"5","key":"465_CR24","doi-asserted-by":"crossref","first-page":"2360","DOI":"10.1137\/09076578X","volume":"31","author":"O Koch","year":"2010","unstructured":"Koch, O., Lubich, C.: Dynamical tensor approximation. SIAM J. Matrix Anal. Appl. 31(5), 2360\u20132375 (2010)","journal-title":"SIAM J. Matrix Anal. Appl."},{"issue":"3","key":"465_CR25","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda, T.G., Bader, B.W.: Tensor decompositions with applications. SIAM Rev. 51(3), 455\u2013500 (2009)","journal-title":"SIAM Rev."},{"key":"465_CR26","doi-asserted-by":"crossref","unstructured":"Kotsia, I., Patras, I.: Support tucker machines. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition, pp. 633\u2013640 (2011)","DOI":"10.1109\/CVPR.2011.5995663"},{"issue":"2","key":"465_CR27","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1007\/s10543-013-0455-z","volume":"54","author":"D Kressner","year":"2014","unstructured":"Kressner, D., Steinlechner, M., Vandereycken, B.: Low-rank tensor completion by Riemannian optimization. BIT Numer. Math. 54(2), 447\u2013468 (2014)","journal-title":"BIT Numer. Math."},{"key":"465_CR28","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1007\/s12561-018-9215-6","volume":"10","author":"X Li","year":"2018","unstructured":"Li, X., Da, X., Zhou, H., Li, L.: Tucker tensor regression and neuroimaging analysis. Stat. Biosci. 10, 520\u2013545 (2018)","journal-title":"Stat. Biosci."},{"issue":"2","key":"465_CR29","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/s40305-019-00245-0","volume":"7","author":"X Li","year":"2019","unstructured":"Li, X., Song, W., Xiu, N.: Optimality conditions for rank-constrained matrix optimization. J. Oper. Res. Soc. China 7(2), 285\u2013301 (2019)","journal-title":"J. Oper. Res. Soc. China"},{"issue":"8","key":"465_CR30","doi-asserted-by":"crossref","first-page":"3755","DOI":"10.1109\/TNNLS.2020.3015477","volume":"32","author":"H Lian","year":"2021","unstructured":"Lian, H.: Learning rate for convex support tensor machines. IEEE Trans. Neural Netw. Learn. Syst. 32(8), 3755\u20133760 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"465_CR31","unstructured":"Liu, J., Musialski, P., Wonka, P., Ye, J.: Tensor completion for estimating missing values in visual data. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 2114\u20132121 (2009)"},{"key":"465_CR32","doi-asserted-by":"crossref","unstructured":"Liu, J., Zhu, C., Long, Z., Liu, Y.: Tensor regression. Found. Trends\u00ae Mach. Learn. 14(4), 379\u2013565 (2021)","DOI":"10.1561\/2200000087"},{"key":"465_CR33","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-74386-4","volume-title":"Tensor Computation for Data Analysis","author":"Y Liu","year":"2022","unstructured":"Liu, Y., Liu, J., Long, Z., Zhu, C.: Tensor Computation for Data Analysis. Springer, Berlin (2022)"},{"issue":"1","key":"465_CR34","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1137\/19M1261043","volume":"2","author":"R Minster","year":"2020","unstructured":"Minster, R., Saibaba, A.K., Kilmer, M.E.: Randomized algorithms for low-rank tensor decompositions in the Tucker format. SIAM J. Math. Data Sci. 2(1), 189\u2013215 (2020)","journal-title":"SIAM J. Math. Data Sci."},{"issue":"5","key":"465_CR35","doi-asserted-by":"crossref","first-page":"2295","DOI":"10.1137\/090752286","volume":"33","author":"I Oseledets","year":"2011","unstructured":"Oseledets, I.: Tensor-train decomposition. SIAM J. Sci. Comput. 33(5), 2295\u20132317 (2011)","journal-title":"SIAM J. Sci. Comput."},{"key":"465_CR36","doi-asserted-by":"crossref","DOI":"10.1007\/978-981-10-8058-6","volume-title":"Tensor Eigenvalues and Their Applications","author":"L Qi","year":"2018","unstructured":"Qi, L., Chen, H., Chen, Y.: Tensor Eigenvalues and Their Applications. Springer, Berlin (2018)"},{"issue":"1","key":"465_CR37","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1137\/20M1323266","volume":"42","author":"L Qi","year":"2021","unstructured":"Qi, L., Chen, Y., Bakshi, M., Zhang, X.: Triple decomposition and tensor recovery of third order tensors. SIAM J. Matrix Anal. Appl. 42(1), 299\u2013329 (2021)","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"465_CR38","doi-asserted-by":"crossref","DOI":"10.1137\/1.9781611974751","volume-title":"Tensor Analysis: Spectral Theory and Special Tensors","author":"L Qi","year":"2017","unstructured":"Qi, L., Luo, Z.: Tensor Analysis: Spectral Theory and Special Tensors. SIAM Press, Philadelphia (2017)"},{"key":"465_CR39","unstructured":"Rabanser, S., Shchur, O., G\u00fcnnemann, S.: Introduction to tensor decompositions and their applications in machine learning. arXiv preprint, arXiv:1711.10781 (2017)"},{"issue":"3","key":"465_CR40","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.1214\/18-AOS1725","volume":"47","author":"G Raskutti","year":"2019","unstructured":"Raskutti, G., Yuan, M., Chen, H.: Convex regularization for high-dimensional multiresponse tensor regression. Ann. Stat. 47(3), 1554\u20131584 (2019)","journal-title":"Ann. Stat."},{"key":"465_CR41","volume-title":"Variational Analysis","author":"RT Rockafellar","year":"2013","unstructured":"Rockafellar, R.T., Wets, B., Roger, J.: Variational Analysis. Springer, Berlin (2013)"},{"issue":"3","key":"465_CR42","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/s10851-012-0406-3","volume":"47","author":"D Russell Luke","year":"2013","unstructured":"Russell Luke, D.: Prox-regularity of rank constraint sets and implications for algorithms. J. Math. Imaging Vis. 47(3), 231\u2013238 (2013)","journal-title":"J. Math. Imaging Vis."},{"issue":"1","key":"465_CR43","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1137\/140957822","volume":"25","author":"R Schneider","year":"2015","unstructured":"Schneider, R., Uschmajew, A.: Convergence results for projected line-search methods on varieties of low-rank matrices via \u0141ojasiewicz inequality. SIAM J. Optim. 25(1), 622\u2013646 (2015)","journal-title":"SIAM J. Optim."},{"issue":"13","key":"465_CR44","doi-asserted-by":"crossref","first-page":"3551","DOI":"10.1109\/TSP.2017.2690524","volume":"65","author":"ND Sidiropoulos","year":"2017","unstructured":"Sidiropoulos, N.D., De Lathauwer, L., Xiao, F., Huang, K., Papalexakis, E.E., Faloutsos, C.: Tensor decomposition for signal processing and machine learning. IEEE Trans. Signal Process. 65(13), 3551\u20133582 (2017)","journal-title":"IEEE Trans. Signal Process."},{"issue":"1","key":"465_CR45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3278607","volume":"13","author":"Q Song","year":"2019","unstructured":"Song, Q., Ge, H., Caverlee, J., Xia, H.: Tensor completion algorithms in big data analytics. ACM Trans. Knowl. Discov. Data 13(1), 1\u201348 (2019)","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"465_CR46","doi-asserted-by":"crossref","unstructured":"Sun, W.W., Hao, B., Li, L.: Tensors in modern statistical learning. Wiley StatsRef: Statistics Reference Online, pp. 1\u201325 (2021)","DOI":"10.1002\/9781118445112.stat08319"},{"key":"465_CR47","first-page":"1","volume":"18","author":"WW Sun","year":"2017","unstructured":"Sun, W.W., Li, L.: STORE: Sparse tensor response regression and neuroimaging analysis. J. Mach. Learn. Res. 18, 1\u201337 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"465_CR48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10115-006-0050-6","volume":"13","author":"D Tao","year":"2007","unstructured":"Tao, D., Li, X., Xindong, W., Weiming, H., Maybank, S.J.: Supervised tensor learning. Knowl. Inf. Syst. 13, 1\u201342 (2007)","journal-title":"Knowl. Inf. Syst."},{"issue":"2","key":"465_CR49","doi-asserted-by":"crossref","first-page":"A1027","DOI":"10.1137\/110836067","volume":"34","author":"N Vannieuwenhoven","year":"2012","unstructured":"Vannieuwenhoven, N., Vandebril, R., Meerbergen, K.: A new truncation strategy for the higher-order singular value decomposition. SIAM J. Sci. Comput. 34(2), A1027\u2013A1052 (2012)","journal-title":"SIAM J. Sci. Comput."},{"key":"465_CR50","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1007\/s10589-021-00287-2","volume":"79","author":"R Wang","year":"2021","unstructured":"Wang, R., Xiu, N., Toh, K.-C.: Subspace quadratic regularization method for group sparse multinomial logistic regression. Comput. Optim. Appl. 79, 531\u2013559 (2021)","journal-title":"Comput. Optim. Appl."},{"key":"465_CR51","doi-asserted-by":"crossref","first-page":"26657","DOI":"10.1007\/s11042-020-10233-9","volume":"80","author":"Yu Xiaotong","year":"2021","unstructured":"Xiaotong, Yu., Luo, Z.: A sparse tensor optimization approach for background subtraction from compressive measurements. Multimedia Tools Appl. 80, 26657\u201326682 (2021)","journal-title":"Multimedia Tools Appl."},{"key":"465_CR52","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.neucom.2020.12.123","volume":"434","author":"Yu Xiaotong","year":"2021","unstructured":"Xiaotong, Yu., Luo, Z., Qi, L., Yanwei, X.: SLRTA: a sparse and low-rank tensor-based approach to internet traffic anomaly detection. Neurocomputing 434, 295\u2013314 (2021)","journal-title":"Neurocomputing"},{"issue":"2","key":"465_CR53","first-page":"415","volume":"10","author":"W Yang","year":"2014","unstructured":"Yang, W., Zhang, L., Song, R.: Optimality conditions for the nonlinear programming problems on Riemannian manifolds. Pacific J. Optim. 10(2), 415\u2013434 (2014)","journal-title":"Pacific J. Optim."},{"key":"465_CR54","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1007\/s10208-015-9269-5","volume":"16","author":"M Yuan","year":"2016","unstructured":"Yuan, M., Zhang, C.-H.: On tensor completion via nuclear norm minimization. Found. Comput. Math. 16, 1031\u20131068 (2016)","journal-title":"Found. Comput. Math."},{"issue":"2","key":"465_CR55","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1137\/19M126476X","volume":"2","author":"A Zhang","year":"2020","unstructured":"Zhang, A., Luo, Y., Raskutti, G., Yuan, M.: ISLET: fast and optimal low-rank tensor regression via importance sketching. SIAM J. Math. Data Sci. 2(2), 444\u2013479 (2020)","journal-title":"SIAM J. Math. Data Sci."},{"key":"465_CR56","unstructured":"Zhao, Q., Zhou, G., Xie, S., Zhang, L., Cichocki, A.: Tensor ring decomposition. arXiv preprint, arXiv:1606.05535 (2016)"},{"issue":"1","key":"465_CR57","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.engappai.2018.04.011","volume":"72","author":"B Zhou","year":"2018","unstructured":"Zhou, B., Song, B., Hassan, M.M., Alamri, A.: Multilinear rank support tensor machine for crowd density estimation. Eng. Appl. Artif. Intell. 72(1), 382\u2013392 (2018)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"502","key":"465_CR58","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1080\/01621459.2013.776499","volume":"108","author":"H Zhou","year":"2013","unstructured":"Zhou, H., Li, L., Zhu, H.: Tensor regression with applications in neuroimaging data analysis. J. Am. Stat. Assoc. 108(502), 540\u2013552 (2013)","journal-title":"J. Am. Stat. Assoc."}],"container-title":["Computational Optimization and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10589-023-00465-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10589-023-00465-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10589-023-00465-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T12:12:57Z","timestamp":1699877577000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10589-023-00465-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,13]]},"references-count":58,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["465"],"URL":"https:\/\/doi.org\/10.1007\/s10589-023-00465-4","relation":{},"ISSN":["0926-6003","1573-2894"],"issn-type":[{"value":"0926-6003","type":"print"},{"value":"1573-2894","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,13]]},"assertion":[{"value":"25 May 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 February 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No potential conflicts of interest were reported by the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}