Tangi Migot

Tangi Migot

Computational Mathematician

Winter 2020 Seminars and a publication

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To celebrate the new year, I gave in January a seminar talk at the Departmental Colloquium Series in Guelph where I motivated the GNEP and presented some of our findings with Monica Cojocaru. In particular, it was based on this new paper we got accepted A dynamical system approach to the generalized Nash equilibrium problem in the open access Journal of Nonlinear and Variational Analysis. The paper reviews the use of nonsmooth dynamical system to find generalized Nash equilibria.

In March, I was taking a break from the canadian winter in France. I gave two seminar talks at Séminaire d’Analyse non linéaire et Optimisation de l’Université d’Avignon and Séminaire du LAMPS de l’Université de Perpignan. Thank you to Térence Bayen and Florent Nacry for inviting me.

The rest of my trip was cancelled due to the covid-19 pandemic. We managed to maintain our workshop on games by turning it into an online event.

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ARCqK published in Mathematical Programming

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I am thrilled to share that the article Scalable adaptive cubic regularization methods has been published in the journal Mathematical Programming, Series A. This has been a really exciting journey with my co-authors Jean-Pierre Dussault and Dominique Orban on this really exciting work that I hope will help explore the numerical possibilities of ARC methods. The proposed implementation is a perfect fit for large-scale application as it solves the subproblem inexactly and only required Hessian-vector products, so no need to evaluate and store the Hessian matrix. As usual, the code has been done in Julia and is available in the folder paper in the Github repository AdaptiveRegularization.jl. Full text published version available from here, enjoy!

Looking Back at the Winter Session

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In the world of numerical optimization, the quest for efficiency, accuracy, and innovation never ceases. At Polytechnique Montréal, students embarking on their educational journey have a unique opportunity to explore this dynamic field through the course MTH8408 Méthodes d’optimisation et contrôle optimal. This course, which I had the privilege of teaching during the winter session of 2023, delves into the depths of numerical methods for optimization, variational calculus, and optimal control.

Unveiling JuliaSmoothOptimizers at JuMP-dev Workshop, JuliaCon 2023

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I am thrilled to share my experiences from the recent JuMP-dev workshop that took place at the JuliaCon 2023, held at MIT in Boston, USA. As a passionate researcher in the field of numerical optimization, this year’s conference was particularly special for me, as it marked my first in-person attendance after the previous year’s online edition (read about it here). You can check the replay of my talk on youtube.

PDENLPModels.jl published in JOSS

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I am very happy to announce the publication in the Journal of Open Source Software of the paper PDENLPModels.jl: A NLPModel API for optimization problems with PDE-constraints.