30 citations · 33 across the 13 of their papers we have counts for
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Full-Low Evaluation Methods For Bound and Linearly Constrained Derivative-Free Optimization
Clément W. Royer, Oumaima Sohab, Luis Nunes Vicente
Derivative-free optimization (DFO) consists in finding the best value of an objective function without relying on derivatives. To tackle such problems, one may build approximate de…
Complexity analysis of regularization methods for implicitly constrained least squares
Akwum Onwunta, Clément W. Royer
Optimization problems constrained by partial differential equations (PDEs) naturally arise in scientific computing, as those constraints often model physical systems or the simulat…
Expected decrease for derivative-free algorithms using random subspaces
Warren Hare, Lindon Roberts, Clément W. Royer
Derivative-free algorithms seek the minimum of a given function based only on function values queried at appropriate points. Although these methods are widely used in practice, the…
Detecting negative eigenvalues of exact and approximate Hessian matrices in optimization
Warren Hare, Clément W. Royer
Nonconvex minimization algorithms often benefit from the use of second-order information as represented by the Hessian matrix. When the Hessian at a critical point possesses negati…
Direct search based on probabilistic descent in reduced spaces
Lindon Roberts, Clément W. Royer
In this paper, we study a generic direct-search algorithm in which the polling directions are defined using random subspaces. Complexity guarantees for such an approach are derived…
A nonlinear conjugate gradient method with complexity guarantees and its application to nonconvex regression
Rémi Chan--Renous-Legoubin, Clément W. Royer
Nonlinear conjugate gradients are among the most popular techniques for solving continuous optimization problems. Although these schemes have long been studied from a global conver…