6 papers
Nonsmooth exact penalty methods for equality-constrained optimization: complexity and implementation
Youssef Diouane, Maxence Gollier, Dominique Orban
Penalty methods are a well known class of algorithms for constrained optimization. They transform a constrained problem into a sequence of unconstrained \emph{penalized} problems i…
A Proximal Modified Quasi-Newton Method for Nonsmooth Regularized Optimization
Youssef Diouane, Mohamed Laghdaf Habiboullah, Dominique Orban
We develop R2N, a modified quasi-Newton method for minimizing the sum of a function and a lower semi-continuous prox-bounded . Both and may be noncon…
Complexity of trust-region methods in the presence of unbounded Hessian approximations
Youssef Diouane, Mohamed Laghdaf Habiboullah, Dominique Orban
We extend traditional complexity analyses of trust-region methods for unconstrained, possibly nonconvex, optimization. Whereas most complexity analyses assume uniform boundedness o…
A Probabilistic U-Net Approach to Downscaling Climate Simulations
Maryam Alipourhajiagha, Pierre-Louis Lemaire, Youssef Diouane +1
Climate models are limited by heavy computational costs, often producing outputs at coarse spatial resolutions, while many climate change impact studies require finer scales. Stati…
A unified error analysis for randomized low-rank approximation with application to data assimilation
Alexandre Scotto Di Perrotolo, Youssef Diouane, Selime Gürol +1
Randomized algorithms have proven to perform well on a large class of numerical linear algebra problems. Their theoretical analysis is critical to provide guarantees on their behav…
An Efficient Scaled spectral preconditioner for sequences of symmetric positive definite linear systems
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We explore a scaled spectral preconditioner for the efficient solution of sequences of symmetric and positive-definite linear systems. We design the scaled preconditioner not only…