{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T22:59:29Z","timestamp":1752361169928,"version":"3.37.3"},"reference-count":65,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T00:00:00Z","timestamp":1704412800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T00:00:00Z","timestamp":1704412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000083","name":"directorate for computer and information science and engineering","doi-asserted-by":"publisher","award":["CCF-2007757"],"award-info":[{"award-number":["CCF-2007757"]}],"id":[{"id":"10.13039\/100000083","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001395","name":"wisconsin alumni research foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001395","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012950","name":"inria","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100012950","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100009465","name":"corfo","doi-asserted-by":"crossref","award":["14ENI-26862"],"award-info":[{"award-number":["14ENI-26862"]}],"id":[{"id":"10.13039\/100009465","id-type":"DOI","asserted-by":"crossref"}]},{"name":"fondecyt","award":["1210362"],"award-info":[{"award-number":["1210362"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Math. Program."],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s10107-023-02040-5","type":"journal-article","created":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T12:02:12Z","timestamp":1704456132000},"page":"319-363","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Complementary composite minimization, small gradients in general norms, and applications"],"prefix":"10.1007","volume":"208","author":[{"given":"Jelena","family":"Diakonikolas","sequence":"first","affiliation":[]},{"given":"Crist\u00f3bal","family":"Guzm\u00e1n","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,5]]},"reference":[{"key":"2040_CR1","unstructured":"Adil, D., Kyng, R., Peng, R., Sachdeva, S: Iterative refinement for $$\\ell _p$$-norm regression. In: Proc.\u00a0ACM-SIAM SODA\u201919 (2019)"},{"key":"2040_CR2","unstructured":"Adil, D., Peng, R., Sachdeva, S.: Fast, provably convergent IRLS algorithm for $$p$$-norm linear regression. In: Proc.\u00a0NeurIPS\u201919 (2019)"},{"key":"2040_CR3","doi-asserted-by":"crossref","unstructured":"Adil, D., Sachdeva, S.: Faster $$p$$-norm minimizing flows, via smoothed $$q$$-norm problems. In: Proc.\u00a0ACM-SIAM SODA\u201920 (2020)","DOI":"10.1137\/1.9781611975994.54"},{"issue":"1","key":"2040_CR4","first-page":"8194","volume":"18","author":"Z Allen-Zhu","year":"2017","unstructured":"Allen-Zhu, Z.: Katyusha: the first direct acceleration of stochastic gradient methods. J. Mach. Learn. Res. 18(1), 8194\u20138244 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"2040_CR5","unstructured":"Allen-Zhu, Z.: How to make the gradients small stochastically: even faster convex and nonconvex SGD. In: Proc.\u00a0NeurIPS\u201918 (2018)"},{"key":"2040_CR6","unstructured":"Altschuler, J., Niles-Weed, J., Rigollet, P.: Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"1","key":"2040_CR7","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1007\/BF01231769","volume":"115","author":"K Ball","year":"1994","unstructured":"Ball, K., Carlen, E.A., Lieb, E.H.: Sharp uniform convexity and smoothness inequalities for trace norms. Invent. Math. 115(1), 463\u2013482 (1994)","journal-title":"Invent. Math."},{"issue":"3","key":"2040_CR8","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1007\/s10957-019-01516-9","volume":"182","author":"HH Bauschke","year":"2019","unstructured":"Bauschke, H.H., Bolte, J., Chen, J., Teboulle, M., Wang, X.: On linear convergence of non-Euclidean gradient methods without strong convexity and Lipschitz gradient continuity. J. Optim. Theory Appl. 182(3), 1068\u20131087 (2019)","journal-title":"J. Optim. Theory Appl."},{"issue":"2","key":"2040_CR9","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1287\/moor.2016.0817","volume":"42","author":"HH Bauschke","year":"2017","unstructured":"Bauschke, H.H., Bolte, J., Teboulle, M.: A descent lemma beyond Lipschitz gradient continuity: first-order methods revisited and applications. Math. Oper. Res. 42(2), 330\u2013348 (2017)","journal-title":"Math. Oper. Res."},{"key":"2040_CR10","series-title":"MOS-SIAM Series on Optimization","doi-asserted-by":"crossref","DOI":"10.1137\/1.9781611974997","volume-title":"First-Order Methods in Optimization","author":"A Beck","year":"2017","unstructured":"Beck, A.: First-Order Methods in Optimization. MOS-SIAM Series on Optimization, SIAM, New Delhi (2017)"},{"issue":"1","key":"2040_CR11","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1137\/080716542","volume":"2","author":"A Beck","year":"2009","unstructured":"Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2(1), 183\u2013202 (2009)","journal-title":"SIAM J. Imaging Sci."},{"issue":"3","key":"2040_CR12","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1090\/S0002-9939-08-09630-5","volume":"137","author":"J Borwein","year":"2009","unstructured":"Borwein, J., Guirao, A.J., H\u00e1jek, P., Vanderwerff, J.: Uniformly convex functions on Banach spaces. Proc. AMS 137(3), 1081\u20131091 (2009)","journal-title":"Proc. AMS"},{"key":"2040_CR13","volume-title":"Techniques of Variational Analysis","author":"JM Borwein","year":"2004","unstructured":"Borwein, J.M., Zhu, Q.J.: Techniques of Variational Analysis. Springer, New York (2004)"},{"issue":"Mar","key":"2040_CR14","first-page":"499","volume":"2","author":"O Bousquet","year":"2002","unstructured":"Bousquet, O., Elisseeff, A.: Stability and generalization. J. Mach. Learn. Res. 2(Mar), 499\u2013526 (2002)","journal-title":"J. Mach. Learn. Res."},{"key":"2040_CR15","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511804441","volume-title":"Convex Optimization","author":"S Boyd","year":"2004","unstructured":"Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)"},{"key":"2040_CR16","doi-asserted-by":"crossref","unstructured":"Bubeck, S., Cohen, M.B., Lee, Y.T., Li, Y.: An homotopy method for $$l_p$$ regression provably beyond self-concordance and in input-sparsity time. In: Proc.\u00a0ACM STOC\u201918 (2018)","DOI":"10.1145\/3188745.3188776"},{"issue":"6","key":"2040_CR17","first-page":"2313","volume":"35","author":"E Cand\u00e9s","year":"2007","unstructured":"Cand\u00e9s, E., Tao, T.: The Dantzig selector: statistical estimation when $$p$$ is much larger than $$n$$. Ann. Stat. 35(6), 2313\u20132351 (2007)","journal-title":"Ann. Stat."},{"key":"2040_CR18","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1137\/22M1481865","volume":"4","author":"A Chambolle","year":"2022","unstructured":"Chambolle, A., Contreras, J.P.: Accelerated Bregman primal-dual methods applied to optimal transport and Wasserstein Barycenter problems. SIAM J. Math. Data Sci. 4, 1369\u20131395 (2022)","journal-title":"SIAM J. Math. Data Sci."},{"issue":"1","key":"2040_CR19","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1007\/s10851-010-0251-1","volume":"40","author":"A Chambolle","year":"2011","unstructured":"Chambolle, A., Pock, T.: A first-order primal-dual algorithm for convex problems with applications to imaging. J. Math. Imaging Vis. 40(1), 120\u2013145 (2011)","journal-title":"J. Math. Imaging Vis."},{"issue":"6","key":"2040_CR20","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1007\/s10208-012-9135-7","volume":"12","author":"V Chandrasekaran","year":"2012","unstructured":"Chandrasekaran, V., Recht, B., Parrilo, P.A., Willsky, A.S.: The convex geometry of linear inverse problems. Found. Comput. Math. 12(6), 805\u2013849 (2012)","journal-title":"Found. Comput. Math."},{"key":"2040_CR21","unstructured":"Cohen, M., Diakonikolas, J., Orecchia, L.: On acceleration with noise-corrupted gradients. In: Proc.\u00a0ICML\u201918, pp. 1019\u20131028 (2018)"},{"key":"2040_CR22","unstructured":"Cohen, M.B., Sidford, A., Tian, K.: Relative Lipschitzness in extragradient methods and a direct recipe for acceleration. In: 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). Schloss Dagstuhl-Leibniz-Zentrum f\u00fcr Informatik (2021)"},{"key":"2040_CR23","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/BF01582220","volume":"67","author":"R Cominetti","year":"1994","unstructured":"Cominetti, R., Mart\u00edn, J.S.: Asymptotic analysis of the exponential penalty trajectory in linear programming. Math. Program. 67, 169\u2013187 (1994)","journal-title":"Math. Program."},{"key":"2040_CR24","unstructured":"Cuturi, M.: Sinkhorn distances: lightspeed computation of optimal transport. In: Burges, C.J.C., Bottou, L. Ghahramani, Z., Weinberger, K.Q. (eds) NIPS, pp. 2292\u20132300 (2013)"},{"issue":"3","key":"2040_CR25","doi-asserted-by":"crossref","first-page":"2384","DOI":"10.1137\/17M1116842","volume":"28","author":"A d\u2019Aspremont","year":"2018","unstructured":"d\u2019Aspremont, A., Guzm\u00e1n, C., Jaggi, M.: Optimal affine-invariant smooth minimization algorithms. SIAM J. Optim. 28(3), 2384\u20132405 (2018)","journal-title":"SIAM J. Optim."},{"issue":"1\u20132","key":"2040_CR26","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/s10107-013-0677-5","volume":"146","author":"O Devolder","year":"2014","unstructured":"Devolder, O., Glineur, F., Nesterov, Y.: First-order methods of smooth convex optimization with inexact oracle. Math. Program. 146(1\u20132), 37\u201375 (2014)","journal-title":"Math. Program."},{"issue":"5","key":"2040_CR27","first-page":"1","volume":"21","author":"J Diakonikolas","year":"2020","unstructured":"Diakonikolas, J., Guzm\u00e1n, C.: Lower bounds for parallel and randomized convex optimization. J. Mach. Learn. Res. 21(5), 1\u201331 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"2040_CR28","unstructured":"Diakonikolas, J., Orecchia, L.: Accelerated extra-gradient descent: a novel accelerated first-order method. In: 9th Innovations in Theoretical Computer Science Conference (ITCS 2018). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2018)"},{"issue":"1","key":"2040_CR29","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1137\/18M1172314","volume":"29","author":"J Diakonikolas","year":"2019","unstructured":"Diakonikolas, J., Orecchia, L.: The approximate duality gap technique: a unified theory of first-order methods. SIAM J. Optim. 29(1), 660\u2013689 (2019)","journal-title":"SIAM J. Optim."},{"key":"2040_CR30","unstructured":"Dragomir, R.-A., Taylor, A., d\u2019Aspremont, A., Bolte, J.: Optimal complexity and certification of Bregman first-order methods. arXiv:1911.08510 (2019)"},{"issue":"1\u20132","key":"2040_CR31","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1007\/s10107-019-01432-w","volume":"185","author":"D Drusvyatskiy","year":"2021","unstructured":"Drusvyatskiy, D., Ioffe, A.D., Lewis, A.S.: Nonsmooth optimization using Taylor-like models: error bounds, convergence, and termination criteria. Math. Program. 185(1\u20132), 357\u2013383 (2021)","journal-title":"Math. Program."},{"issue":"3","key":"2040_CR32","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1287\/moor.2017.0889","volume":"43","author":"D Drusvyatskiy","year":"2018","unstructured":"Drusvyatskiy, D., Lewis, A.S.: Error bounds, quadratic growth, and linear convergence of proximal methods. Math. Oper. Res. 43(3), 919\u2013948 (2018)","journal-title":"Math. Oper. Res."},{"key":"2040_CR33","unstructured":"Dvurechensky, P., Gasnikov, A., Kroshnin, A.: Computational optimal transport: complexity by accelerated gradient descent is better than by Sinkhorn\u2019s algorithm. In: International Conference on Machine Learning, pp. 1367\u20131376. PMLR (2018)"},{"key":"2040_CR34","unstructured":"Ene, A., Vladu, A.: Improved convergence for $$\\ell _1$$ and $$\\ell _{\\infty }$$ regression via iteratively reweighted least squares. In: Proc.\u00a0ICML\u201919 (2019)"},{"issue":"2","key":"2040_CR35","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/BF01417214","volume":"36","author":"S-C Fang","year":"1992","unstructured":"Fang, S.-C.: An unconstrained convex programming view of linear programming. ZOR Methods Model. Oper. Res. 36(2), 149\u2013161 (1992)","journal-title":"ZOR Methods Model. Oper. Res."},{"key":"2040_CR36","unstructured":"Feldman, V.: Generalization of erm in stochastic convex optimization: The dimension strikes back. In: Advances in Neural Information Processing Systems, vol. 29 (2016)"},{"issue":"1","key":"2040_CR37","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1134\/S0965542518010050","volume":"58","author":"AV Gasnikov","year":"2018","unstructured":"Gasnikov, A.V., Nesterov, Y.E.: Universal method for stochastic composite optimization problems. Comput. Math. Math. Phys. 58(1), 48\u201364 (2018)","journal-title":"Comput. Math. Math. Phys."},{"issue":"1","key":"2040_CR38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jco.2014.08.003","volume":"31","author":"C Guzm\u00e1n","year":"2015","unstructured":"Guzm\u00e1n, C., Nemirovski, A.: On lower complexity bounds for large-scale smooth convex optimization. J. Complex. 31(1), 1\u201314 (2015)","journal-title":"J. Complex."},{"issue":"2","key":"2040_CR39","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1007\/s10589-014-9723-3","volume":"61","author":"N He","year":"2015","unstructured":"He, N., Juditsky, A.B., Nemirovski, A.: Mirror Prox algorithm for multi-term composite minimization and semi-separable problems. Comput. Optim. Appl. 61(2), 275\u2013319 (2015)","journal-title":"Comput. Optim. Appl."},{"key":"2040_CR40","unstructured":"Jambulapati, A., Sidford, A., Tian, K.: A direct tildeO(1\/epsilon) iteration parallel algorithm for optimal transport. In: Wallach, H.M., Larochelle, H., Beygelzimer, A., d\u2019Alch\u00e9-Buc, F., Fox, E.B., Garnett, R. (eds) Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8\u201314, 2019, Vancouver, BC, Canada, pp. 11355\u201311366 (2019)"},{"key":"2040_CR41","unstructured":"Juditsky, A. Nemirovski, A.S.: Large deviations of vector-valued martingales in 2-smooth normed spaces. arXiv:0809.0813 (2008)"},{"issue":"1","key":"2040_CR42","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1287\/10-SSY010","volume":"4","author":"A Juditsky","year":"2014","unstructured":"Juditsky, A., Nesterov, Y.: Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization. Stoch. Syst. 4(1), 44\u201380 (2014)","journal-title":"Stoch. Syst."},{"key":"2040_CR43","doi-asserted-by":"crossref","unstructured":"Kim, D., Fessler, J.A.: Optimizing the efficiency of first-order methods for decreasing the gradient of smooth convex functions. J. Optim. Theory Appl. 188, 192\u2013219 (2020)","DOI":"10.1007\/s10957-020-01770-2"},{"issue":"1\/2","key":"2040_CR44","first-page":"173","volume":"2","author":"AS Lewis","year":"1995","unstructured":"Lewis, A.S.: The convex analysis of unitarily invariant matrix functions. J. Convex Anal. 2(1\/2), 173\u2013183 (1995)","journal-title":"J. Convex Anal."},{"issue":"137","key":"2040_CR45","first-page":"1","volume":"23","author":"T Lin","year":"2022","unstructured":"Lin, T., Ho, N., Jordan, M.I.: On the efficiency of entropic regularized algorithms for optimal transport. J. Mach. Learn. Res. 23(137), 1\u201342 (2022)","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"2040_CR46","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1137\/16M1099546","volume":"28","author":"H Lu","year":"2018","unstructured":"Lu, H., Freund, R.M., Nesterov, Y.: Relatively smooth convex optimization by first-order methods, and applications. SIAM J. Optim. 28(1), 333\u2013354 (2018)","journal-title":"SIAM J. Optim."},{"issue":"2","key":"2040_CR47","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/0041-5553(85)90100-4","volume":"25","author":"AS Nemirovskii","year":"1985","unstructured":"Nemirovskii, A.S., Nesterov, Y.E.: Optimal methods of smooth convex minimization. USSR Comput. Math. Math. Phys. 25(2), 21\u201330 (1985)","journal-title":"USSR Comput. Math. Math. Phys."},{"key":"2040_CR48","unstructured":"Nemirovskii, A.S., Yudin: Problem Complexity and Method Efficiency in Optimization. Wiley, Hoboken (1983)"},{"issue":"2","key":"2040_CR49","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/0885-064X(91)90001-E","volume":"7","author":"AS Nemirovsky","year":"1991","unstructured":"Nemirovsky, A.S.: On optimality of krylov\u2019s information when solving linear operator equations. J. Complex. 7(2), 121\u2013130 (1991)","journal-title":"J. Complex."},{"issue":"2","key":"2040_CR50","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/0885-064X(92)90013-2","volume":"8","author":"AS Nemirovsky","year":"1992","unstructured":"Nemirovsky, A.S.: Information-based complexity of linear operator equations. J. Complex. 8(2), 153\u2013175 (1992)","journal-title":"J. Complex."},{"issue":"1","key":"2040_CR51","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s10107-012-0629-5","volume":"140","author":"Y Nesterov","year":"2013","unstructured":"Nesterov, Y.: Gradient methods for minimizing composite functions. Math. Program. 140(1), 125\u2013161 (2013)","journal-title":"Math. Program."},{"issue":"1\u20132","key":"2040_CR52","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s10107-014-0790-0","volume":"152","author":"Y Nesterov","year":"2015","unstructured":"Nesterov, Y.: Universal gradient methods for convex optimization problems. Math. Program. 152(1\u20132), 381\u2013404 (2015)","journal-title":"Math. Program."},{"key":"2040_CR53","first-page":"10","volume":"88","author":"Y Nesterov","year":"2012","unstructured":"Nesterov, Y.: How to make the gradients small. Optima Math. Optim. Soc. Newsl. 88, 10\u201311 (2012)","journal-title":"Optima Math. Optim. Soc. Newsl."},{"key":"2040_CR54","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1017\/S096249291300007X","volume":"22","author":"Y Nesterov","year":"2013","unstructured":"Nesterov, Y., Nemirovski, A.: On first-order algorithms for $$\\ell _1$$\/nuclear norm minimization. Acta Numer. 22, 509 (2013)","journal-title":"Acta Numer."},{"issue":"3","key":"2040_CR55","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1137\/070697835","volume":"52","author":"B Recht","year":"2010","unstructured":"Recht, B., Fazel, M., Parrilo, P.A.: Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM Rev. 52(3), 471\u2013501 (2010)","journal-title":"SIAM Rev."},{"key":"2040_CR56","volume-title":"Convex Analysis. Princeton Mathematical Series","author":"R Tyrrell Rockafellar","year":"1970","unstructured":"Tyrrell Rockafellar, R.: Convex Analysis. Princeton Mathematical Series. Princeton University Press, Princeton (1970)"},{"issue":"3","key":"2040_CR57","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1007\/s10208-014-9189-9","volume":"14","author":"K Scheinberg","year":"2014","unstructured":"Scheinberg, K., Goldfarb, D., Bai, X.: Fast first-order methods for composite convex optimization with backtracking. Found. Comput. Math. 14(3), 389\u2013417 (2014)","journal-title":"Found. Comput. Math."},{"key":"2040_CR58","first-page":"2635","volume":"11","author":"S Shalev-Shwartz","year":"2010","unstructured":"Shalev-Shwartz, S., Shamir, O., Srebro, N., Sridharan, K.: Learnability, stability and uniform convergence. J. Mach. Learn. Res. 11, 2635\u20132670 (2010)","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"2040_CR59","doi-asserted-by":"crossref","first-page":"171","DOI":"10.2140\/pjm.1958.8.171","volume":"8","author":"M Sion","year":"1958","unstructured":"Sion, M.: On general minimax theorems. Pac. J. Math. 8(1), 171\u2013176 (1958)","journal-title":"Pac. J. Math."},{"key":"2040_CR60","unstructured":"Srebro, N., Sridharan, K.: On convex optimization, fat shattering and learning. unpublished note (2012)"},{"key":"2040_CR61","unstructured":"Tseng, P.: On accelerated proximal gradient methods for convex-concave optimization. Manuscript, 1 (2008)"},{"key":"2040_CR62","unstructured":"Weed, J.: An explicit analysis of the entropic penalty in linear programming. In: Bubeck, S., Perchet, V., Rigollet, P. (eds.) Conference on Learning Theory, COLT 2018, Stockholm, Sweden, 6\u20139 July 2018, Volume\u00a075 of Proceedings of Machine Learning Research, pp. 1841\u20131855 (2018)"},{"key":"2040_CR63","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/0022-247X(83)90112-9","volume":"95","author":"C Zalinescu","year":"1983","unstructured":"Zalinescu, C.: On uniformly convex functions. J. Math. Anal. Appl. 95, 344\u2013374 (1983)","journal-title":"J. Math. Anal. Appl."},{"key":"2040_CR64","doi-asserted-by":"crossref","DOI":"10.1142\/5021","volume-title":"Convex Analysis in General Vector Spaces","author":"C Zalinescu","year":"2002","unstructured":"Zalinescu, C.: Convex Analysis in General Vector Spaces. World Scientific, Singapore (2002)"},{"issue":"2","key":"2040_CR65","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou, H., Hastie, T.: Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B (Stat. Methodol.) 67(2), 301\u2013320 (2005)","journal-title":"J. R. Stat. Soc. Ser. B (Stat. Methodol.)"}],"container-title":["Mathematical Programming"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10107-023-02040-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10107-023-02040-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10107-023-02040-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,15]],"date-time":"2024-10-15T16:08:54Z","timestamp":1729008534000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10107-023-02040-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,5]]},"references-count":65,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["2040"],"URL":"https:\/\/doi.org\/10.1007\/s10107-023-02040-5","relation":{},"ISSN":["0025-5610","1436-4646"],"issn-type":[{"type":"print","value":"0025-5610"},{"type":"electronic","value":"1436-4646"}],"subject":[],"published":{"date-parts":[[2024,1,5]]},"assertion":[{"value":"18 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 January 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}