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20072026
most citedHidden Convexity in the l0 Pseudonorm

9 citations · 33 across the 49 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

math.OC2020

Constant Along Primal Rays Conjugacies and Generalized Convexity for Functions of the Support

Jean-Philippe Chancelier, Michel de Lara

The support of a vector in R d is the set of indices with nonzero entries. Functions of the support have the property to be 0-homogeneous and, because of that, the Fenchel conjugac…

math.OC2020

Tropical Dynamic Programming for Lipschitz Multistage Stochastic Programming

Marianne Akian, Jean-Philippe Chancelier, Benoît Tran

We present an algorithm called Tropical Dynamic Programming (TDP) which builds upper and lower approximations of the Bellman value functions in risk-neutral Multistage Stochastic P…

math.OC2020

Kuhn's Equivalence Theorem for Games in Intrinsic Form

Benjamin Heymann, Michel de Lara, Jean-Philippe Chancelier

We state and prove Kuhn's equivalence theorem for a new representation of games, the intrinsic form. First, we introduce games in intrinsic form where information is represented by…

math.OC2020

A Decomposition Method by Interaction Prediction for the Optimization of Maintenance Scheduling

Jean-Philippe Chancelier, Thomas Bittar, Pierre Carpentier +2

Optimizing maintenance scheduling is a major issue to improve the performance of hydropower plants. We study a system of several physical components of the same family: either a se…

math.OC2020★ 2 cited

Capra-Convexity, Convex Factorization and Variational Formulations for the l0 Pseudonorm

Jean-Philippe Chancelier, Michel de Lara

The so-called l0 pseudonorm, or cardinality function, counts the number of nonzero components of a vector. In this paper, we analyze the l0 pseudonorm by means of so-called Capra (…

math.OC2020

Constant Along Primal Rays Conjugacies and the l0 Pseudonorm

Jean-Philippe Chancelier, Michel de Lara

The so-called l0 pseudonorm on Rd counts the number of nonzero components of a vector. It is used in sparse optimization, either as criterion or in the constraints, to obtain solut…