709 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université Toulouse III - Paul SabatierFR432 papers
- Université Toulouse - Jean JaurèsFR332 papers
- Université Toulouse-I-CapitoleFR331 papers
- Institut Polytechnique de BordeauxFR326 papers
- Centre National de la Recherche ScientifiqueFR253 papers
- Université de ToulouseFR159 papers
- Institut National Polytechnique de ToulouseFR101 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR92 papers
- École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des TélécommunicationsFR52 papers
- Institut national de recherche en sciences et technologies du numériqueFR26 papers
- Institut Universitaire de FranceFR19 papers
- Sorbonne UniversitéFR19 papers
31 papers · 1 filter
Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization
Serge Gratton, Alena Kopaničáková, Philippe Toint
Two OFFO (Objective-Function Free Optimization) noise tolerant algorithms are presented that handle bound constraints, inexact gradients and use second-order information when avail…
Proximal Operators of Sorted Nonconvex Penalties
Anne Gagneux, Mathurin Massias, Emmanuel Soubies
This work studies the problem of sparse signal recovery with automatic grouping of variables. To this end, we investigate sorted nonsmooth penalties as a regularization approach fo…
Sample complexity of optimal transport barycenters with discrete support
Léo Portales, Edouard Pauwels, Elsa Cazelles
Computational implementation of optimal transport barycenters for a set of target probability measures requires a form of approximation, a widespread solution being empirical appro…
Box-constrained L0 Bregman-relaxations
Mhamed Essafri, Luca Calatroni, Emmanuel Soubies
Regularization using the L0 pseudo-norm is a common approach to promote sparsity, with widespread applications in machine learning and signal processing. However, solving such prob…
Bilevel gradient methods and the Morse parametric qualification condition
Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels +1
We introduce the Morse parametric qualification condition for bilevel programming. Generic semi-algebraic functions are Morse parametric in a piecewise sense. Thus, bilevel program…
A Stochastic Objective-Function-Free Adaptive Regularization Method with Optimal Complexity
Serge Gratton, Sadok Jerad, Philippe L. Toint
A fully stochastic second-order adaptive-regularization method for unconstrained nonconvex optimization is presented which never computes the objective-function value, but yet achi…
One-step differentiation of iterative algorithms
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
In appropriate frameworks, automatic differentiation is transparent to the user at the cost of being a significant computational burden when the number of operations is large. For…
Energy Management System for a Low Voltage Direct Current Microgrid: Modeling and experimental validation
Yanandlall Gopee, Margot Gaetani-Liseo, Anne Blavette +3
In the field of microgrids with a significant integration of Renewable Energy Sources, the efficient and practical power storage systems requirement is causing DC microgrids to gai…
On the nature of Bregman functions
Edouard Pauwels
Let C be convex, compact, with nonempty interior and h be Legendre with domain C, continuous on C. We prove that h is Bregman if and only if it is strictly convex on C and C is a p…
Singular versus boundary arcs for aircraft trajectory optimization in climbing phase
Olivier Cots, Joseph Gergaud, Damien Goubinat +1
In this article, we are interested in optimal aircraft trajectories in climbing phase. We consider the cost index criterion which is a convex combination of the time-to-climb and t…
Does 3D frequency-domain FWI of full-azimuth/long-offset OBN data feasible? The Gorgon case study
S. Operto, P. Amestoy, H. S. Aghamiry +13
Frequency-domain Full Waveform Inversion (FWI) is potentially amenable to efficient processing of full-azimuth long-offset stationary-recording seabed acquisition carried out with…
The derivatives of Sinkhorn-Knopp converge
Edouard Pauwels, Samuel Vaiter
We show that the derivatives of the Sinkhorn-Knopp algorithm, or iterative proportional fitting procedure, converge towards the derivatives of the entropic regularization of the op…
Automatic differentiation of nonsmooth iterative algorithms
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
Differentiation along algorithms, i.e., piggyback propagation of derivatives, is now routinely used to differentiate iterative solvers in differentiable programming. Asymptotics is…
Complexity and performance for two classes of noise-tolerant first-order algorithms
S. Gratton, S. Jerad, Ph. L. Toint
Two classes of algorithms for optimization in the presence of noise are presented, that do not require the evaluation of the objective function. The first generalizes the well-know…
Inertial Newton Algorithms Avoiding Strict Saddle Points
Camille Castera
We study the asymptotic behavior of second-order algorithms mixing Newton's method and inertial gradient descent in non-convex landscapes. We show that, despite the Newtonian behav…
COL0RME: Super-resolution microscopy based on sparse blinking/fluctuating fluorophore localization and intensity estimation
Vasiliki Stergiopoulou, Luca Calatroni, José Henrique de Morais Goulart +2
To overcome the physical barriers caused by light diffraction, super-resolution techniques are often applied in fluorescence microscopy. State-of-the-art approaches require specifi…
Hölder Gradient Descent and Adaptive Regularization Methods in Banach Spaces for First-Order Points
Serge Gratton, Sadok Jerad, Philippe L. Toint
This paper considers optimization of smooth nonconvex functionals in smooth infinite dimensional spaces. A Hölder gradient descent algorithm is first proposed for finding approxima…
Conservative parametric optimality and the ridge method for tame min-max problems
Edouard Pauwels
We study the ridge method for min-max problems, and investigate its convergence without any convexity, differentiability or qualification assumption. The central issue is to determ…
A Sublevel Moment-SOS Hierarchy for Polynomial Optimization
Tong Chen, Jean-Bernard Lasserre, Victor Magron +1
We introduce a sublevel Moment-SOS hierarchy where each SDP relaxation can be viewed as an intermediate (or interpolation) between the d-th and (d+1)-th order SDP relaxations of th…
COL0RME: COvariance-based super-Resolution Microscopy with intensity Estimation
Vasiliki Stergiopoulou, José Henrique de Morais Goulart, Sébastien Schaub +2
Super-resolution light microscopy overcomes the physical barriers due to light diffraction, allowing for the observation of otherwise indistinguishable subcellular entities. Howeve…
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks
Tong Chen, Jean-Bernard Lasserre, Victor Magron +1
The Lipschitz constant of a network plays an important role in many applications of deep learning, such as robustness certification and Wasserstein Generative Adversarial Network.…
Tangency property and prior-saturation points in minimal time problems in the plane
Térence Bayen, Olivier Cots
In this paper, we consider minimal time problems governed by control-affine-systems in the plane, and we focus on the synthesis problem in presence of a singular locus that involve…
A Zermelo navigation problem with a vortex singularity
Bernard Bonnard, Olivier Cots, Boris Wembe
Helhmoltz-Kirchhoff equations of motions of vortices of an incompressible fluid in the plane define a dynamics with singularities and this leads to a Zermelo navigation problem des…
Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learning
Jérôme Bolte, Edouard Pauwels
Modern problems in AI or in numerical analysis require nonsmooth approaches with a flexible calculus. We introduce generalized derivatives called conservative fields for which we d…