Anna Korba

merci Mathurin !!

merci David !!

thanks Arthur !!

See akorba.github.io/Optinfinite.... for details and updates. Job openings will come soon.

I'm thrilled to announce that my #ERCStG project **Optinfinite : Efficient infinite-dimensional optimization over measures**
has been accepted. Thank you
@erc.europa.eu !
Many thanks also to @crestumr.bsky.social @ipparis.bsky.social for they support, as well as to my collaborators and friends.

Mark your calendars !
🏔️Machine Learning Autumn School at Aussois (France). 🏔️
16-21 nov 2025.
Submission deadline to present your work via talk or poster: 28th of April.
mlataussois.sciencesconf.org
Great line-up of speakers ! ⬇️

Invited speakers include

Gabriel Victorino Cardoso (Mines Paris PSL)
Solenne Gaucher (ENSAE)
Thomas Moreau (INRIA)
Mathilde Mougeot (ENS Paris-Saclay, ensiEE)

... and more to come !

more info + detailed program upcoming on the website 👀

✏️ Courses:

Optimisation, Adrien Taylor (INRIA, ENS)

Federated Learning, Aymeric Dieuleveut (Polytechnique)

Sampling and Generative Models, Marylou Gabrié (ENS PSL)

Evasion Attacks in AI, Rafaël Pinot (Sorbonne)

Mark your calendars !
🏔️Machine Learning Autumn School at Aussois (France). 🏔️
16-21 nov 2025.
Submission deadline to present your work via talk or poster: 28th of April.
mlataussois.sciencesconf.org
Great line-up of speakers ! ⬇️

Applications are open for the Machine Learning Crash Course (MLCC 2019) to be held in Genoa, the heart of the Italian riviera, on June 17-21, 2019.

For more information, visit the course website atApply *BEFORE* April 19th.

#MachineLearning

lnkd.in/ecSCmih

📣 Hiring! I am looking for PhD/postdoc candidates to work on foundation models for science at @ULiege, with a special focus on weather and climate systems. 🌏 Three positions are open around deep learning, physics-informed FMs and inverse problems with FMs.

Mirror and Preconditioned Gradient Descent in Wasserstein Space As the problem of minimizing functionals on the Wasserstein space encompasses many applications in machine learning, different optimization algorithms on $\mathbb{R}^d$ have received their counterpart...

Glad to announce that our work "Mirror and Preconditioned Gradient Descent in Wasserstein Space" was accepted at #NeurIPS2024 as a spotlight!

This is a joint work with the amazing T. Uscidda, A. David, P.C. Aubin-Frankowski and A. Korba!

Link: arxiv.org/abs/2406.08938