# Changelog & News

This page is a changelog & news for my website (reverse chronological).

## 2024

*October 1*: Jean-Jacques Godeme is joining me as a postdoc to work on automatic differentiation. Welcome!*September 26*: Just learned that I will be a 3IA chair holder for the next 4 years for my project BOGL (Bilevel Optimization for Graph Learning).*September 26*: Our (w/ F. Iutzeler & E. Pauwels) paper Derivatives of Stochastic Gradient Descent was accepted to NeurIPS 2024. _*September 23-25*: We organized with L. Calatroni the LOCA workshop in Sophie-Antipolis. _*September 10*: I gave a talk at the Statistical and Probabilistic Analysis of Random Networks and Processes conference.*September 2*: Started my tweet serie "One Piece of Math a Day" on Twitter. Also available on my website here.*July 9*: I gave a talk at Inria Grenoble on automatic differentiation.*July 1-3*: Attending EURO 2024. I will give an invited talk in the "Algorithms for machine learning and inverse problems" session.*June 27*: The grant ANR PRC MAD was just accepted. I will be the PI of the project "Mathematics of Automatic Differentiation" for the next 4 years with the following consortium: J. Bolte, S. Gadat, E. Pauwels (Toulouse School of Economics), G. Fort, F. Iutzeler (Université Paul Sabatier) and J.-B. Caillau, Y. Laguel (Université Côte d'Azur).*June 23-30*: Visiting G. Gidel at MILA. I gave a talk at MTL Opt.*June 15*: Accepted paper to TMLR with Hashem Ghanem and Nicolas Keriven Gradient Scarcity with Bilevel Optimization for Graph Learning with Featured Certification!*May 28*: New preprint with Sophie Jaffard and Patricia Reynaud-Bouret CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration.*May 21*: New preprint with Franck Iutzeler and Edouard Pauwels on the Derivatives of Stochastic Gradient Descent.*April 9*: Our blogpost with Mathieu Dagréou, Pierre Ablin and Thomas Moreau How to compute Hessian-vector products? was accepted to ICLR 2024 as*spotlight*.*March 1-9*: Visiting A. Bietti at CCM, Flatiron Institute, NYC. I presented our work on iterative automatic differentiation.*January 24*: Talk at the kickoff meeting of the PEPR PDE-AI project.*January 20*: Our papers Provable local learning rule by expert aggregation for a Hawkes network and A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization were accepted to AISTATS 2024.