518 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université Toulouse III - Paul SabatierFR332 papers
- Institut de Recherche en Informatique de ToulouseFR331 papers
- Université Toulouse - Jean JaurèsFR329 papers
- Institut Polytechnique de BordeauxFR326 papers
- Centre National de la Recherche ScientifiqueFR159 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR78 papers
- Université de ToulouseFR51 papers
- Institut National Polytechnique de ToulouseFR43 papers
- Toulouse School of EconomicsFR31 papers
- École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des TélécommunicationsFR20 papers
- Institut national de recherche en sciences et technologies du numériqueFR16 papers
- Institut de Mathématiques de ToulouseFR15 papers
4 papers · 2 filters
Mixed-Strategy Equilibria in the War of Attrition under Uncertainty
Jean-Paul Décamps, Fabien Gensbittel, Thomas Mariotti
We study a generic family of two-player continuous-time nonzero-sum stopping games modeling a war of attrition with symmetric information and stochastic payoffs that depend on an h…
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…
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…