{"title":"Corrigendum and Addendum: Newton Differentiability of Convex Functions in Normed Spaces and of a Class of Operators","authors":"Martin Brokate, Michael Ulbrich","doi":"10.1137/24m1669542","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Optimization, Volume 34, Issue 3, Page 3163-3166, September 2024. <br/> Abstract. As it is formulated, Proposition 3.12 of [M. Brokate and M. Ulbrich, SIAM J. Optim., 32 (2022), pp. 1265–1287] contains an error. But this can be corrected in the way described below. The results of [M. Brokate and M. Ulbrich, SIAM J. Optim., 32 (2022), pp. 1265–1287] based on Proposition 3.12 are not affected. We also use the opportunity to add a further illustrating example and to rectify some inaccuracies which may be confusing.","PeriodicalId":49529,"journal":{"name":"SIAM Journal on Optimization","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/24m1669542","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
SIAM Journal on Optimization, Volume 34, Issue 3, Page 3163-3166, September 2024. Abstract. As it is formulated, Proposition 3.12 of [M. Brokate and M. Ulbrich, SIAM J. Optim., 32 (2022), pp. 1265–1287] contains an error. But this can be corrected in the way described below. The results of [M. Brokate and M. Ulbrich, SIAM J. Optim., 32 (2022), pp. 1265–1287] based on Proposition 3.12 are not affected. We also use the opportunity to add a further illustrating example and to rectify some inaccuracies which may be confusing.
期刊介绍：
The SIAM Journal on Optimization contains research articles on the theory and practice of optimization. The areas addressed include linear and quadratic programming, convex programming, nonlinear programming, complementarity problems, stochastic optimization, combinatorial optimization, integer programming, and convex, nonsmooth and variational analysis. Contributions may emphasize optimization theory, algorithms, software, computational practice, applications, or the links between these subjects.
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