I presented our recent work on loss landscape characterization during NeurIPS@Paris workhsop poster session. My travel was supported by the organizers of the workshop. In this work, we propose a class of functions that better captures the properties of loss landscape of neural networks.

I am happy to announce that I have one paper accepted to NeurIPS 2024 on a novel class of functions that neural networks represent. This class contains functions with saddles and local minima in contrast to previous works. This is a joint work with Niccolò Ajroldi , Antonio Orvieto, and Aurelien Lucchi. It is now available on arXiv.

New paper on decentralized training with contractive compressed communication. We achieve near-optimal convergence guarantees using Error Feedback and momentum tracking.

I attended KAUST Rising Stars in AI Symposium organized by KAUST AI Initiatve. As a part of the symposium, I gave a talk on AsGrad project.

I am thrilled to announce that AsGrad paper has been accepted to AISTATS 2024. In this paper we propose a unified framework to analyze asynchronous SGD-type algorithms covering many existing versions.