Sierra Team @Sierra_ML_Lab
Twitter account of the Sierra project-team @Inria_Paris, @CNRS, @ENS_ULM #MachineLearning & #Optimization di.ens.fr/sierra/ Paris Joined March 2021-
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Tired of lengthy computations to derive scaling laws? This post is made for you: discover the sharpness of the z-transform! francisbach.com/z-transform/
Happy to have our recent papers on conformal prediction with e-values presented at COLT by my advisor @BachFrancis! Full details here: 📚arxiv.org/abs/2503.13050 📚arxiv.org/abs/2505.13732 #COLT2025
For good probability predictions, you should use post-hoc calibration. With @Eugene_Berta, Michael Jordan, and @BachFrancis we argue that early stopping and tuning should account for this! Using the loss after post-hoc calibration often avoids premature stopping. 🧵1/
I’ll be presenting our paper at COLT in Lyon this Monday at the Predictions and Uncertainty workshop — come say hi if you're around! 👋 Check out @DHolzmueller's thread below 👇 #COLT2025
I’ll be presenting our paper at COLT in Lyon this Monday at the Predictions and Uncertainty workshop — come say hi if you're around! 👋 Check out @DHolzmueller's thread below 👇 #COLT2025
Characterizing finely the decay of eigenvalues of kernel matrices: many people need it, but explicit references are hard to find. This blog post reviews amazing asymptotic results from Harold Widom (1963!) and proposes new non-asymptotic bounds. francisbach.com/spectrum-kerne…
A free book: Learning Theory from First Principles by @BachFrancis It covers a bunch of key topics from machine learning (ML) theory and practice, such as: - Math basics - Supervised learning - Generalization, overfitting & adaptivity - Tools to design learning algorithms -…
Michael Jordan is indeed one of the greatest thinkers in the history of AI 🐐 Economics, incentives (mechanism design), information flow, creativity, cooperation, greed and power struggles are important topics that we crucially need to understand better for the benefit of…
Michael Jordan is indeed one of the greatest thinkers in the history of AI 🐐 Economics, incentives (mechanism design), information flow, creativity, cooperation, greed and power struggles are important topics that we crucially need to understand better for the benefit of…
[🔴#IAScienceSociety] @BachFrancis (@inria_paris-@ENS_ParisSaclay) participe au symposium "The Mathematics of #MachineLearning" aux côtés de @gabrielpeyre, Gilles Louppe (@UniversiteLiege), Gersende Fort (@CNRS) et Vianney Perchet (@INSAE @IP_Paris_).
🔴 @Inria est présent à la conférence "AI,Science and society" à @IP_Paris_, prélude au #SommetActionIA et sous la direction du Pr. Michael Jordan (@UCBerkeley-@Inria) ! L'événement a été inauguré ce matin par Michael Jordan et cet après-midi par @ClaraChappaz 🗣
My book is (at last) out, just in time for Christmas! A blog post to celebrate and present it: francisbach.com/my-book-is-out/
Bravo Bertille et Marc!
🎓#PhDs | Félicitations à Juliette Murris et Alice Rogier de l’équipe @TeamHeka (@univ_paris_cite, @CRCordeliers, @Inserm) ainsi qu'à @oumaymabounou et Céline Moucer des équipes WILLOW et @Sierra_ML_Lab (@CNRSinformatics, @ENS_ULM) qui ont soutenu leur #thèse en octobre 🎉👏 !
#ERCStG 🏆 | Félicitations à @TaylorAdrien, chargé de recherche @Inria au centre @Inria_paris, membre de l'équipe-projet commune @Sierra_ML_Lab (@CNRS @CNRSinformatics @ENS_ULM), lauréat d'une ERC Starting Grant 👏 Découvrez son portrait et son projet 👉 buff.ly/3YlTBU6
How fast is gradient descent, *for real*? Some (partial) answers in this new blog post on scaling laws for optimization. francisbach.com/scaling-laws-o…
Bravo Adrien!
🙎♂️🔬 #30minScience | Aujourd’hui, au centre @Inria de #Paris, @umutsimsekli (@Sierra_ML_Lab) nous présente une demi-heure de science consacrée aux #Fractales : ”Fractals in Machine Learning”. 🔎 Découvrez en plus sur Umut et ses recherches dans : di.ens.fr/umut.simsekli/…
The blog is back in 2024, with a first post on unraveling spectral properties of kernel matrices! francisbach.com/spectrum-kerne…
Bravo Julien!!
@orvieto_antonio and I are planning to co-advise a student from this program. If you are interested in optimization for deep learning, please apply!
@orvieto_antonio and I are planning to co-advise a student from this program. If you are interested in optimization for deep learning, please apply!
Au département d’informatique de l’ENS, le CNRS et Inria main dans la main dans l’effort. #LEtapeduTour Bravo @olivier_cappe!

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