https://pure.iiasa.ac.at/id/eprint/14043 2021-08-27T17:41:40Z info:eu-repo/semantics/descriptiveMetadata https://pure.iiasa.ac.at/id/eprint/14043/ Optimisation non Differentiable: Methodes de Faisceaux Lemarechal, C. We define a class of descent methods to minimize a nondifferentiable function. These methods are based on a representation of the objective which combines a quadratic approximation and the usual approximation by a piecewise linear function. Hence, they realize a synthesis between quasi-Newton methods and cutting plane methods. In addition, they have the particularity of requiring no sophisticated line search. They are also presented in ref. [7] (in English). Springer Berlin Heidelberg Glowinski, R. Lions, J.L. Liboria, I. 2006 Book Section PeerReviewed Lemarechal, C. <https://pure.iiasa.ac.at/view/iiasa/2110.html> (2006). Optimisation non Differentiable: Methodes de Faisceaux. In: Computing Methods in Applied Sciences and Engineering, 1977, I. Eds. Glowinski, R., Lions, J.L., & Liboria, I., pp. 53-61 Germany: Springer Berlin Heidelberg. ISBN 978-3-540-35411-6 10.1007/BFb0063614 <https://doi.org/10.1007/BFb0063614>. 10.1007/BFb0063614 10.1007/BFb0063614 10.1007/BFb0063614 info:eu-repo/semantics/humanStartPage