Our FedNL paper has been accepted to ICML workshops: International Workshop on Federated Learning for User Privacy and Data Confidentiality and Beyond first-order methods in ML systems. The paper will be presented as a poster at the first workshop and as a prerecorded video at the second one.

I am attending PRAIRE/MIAI Artificial Intelligence Summer School (PAISS 2021) (this year virtually only). This summer school is organized by PRAIRIE, MIAI, NAVER LABS Europe, and INRIA. The summer school comprises lectures conducted by renowned experts in different areas of artificial intelligence. As a part of the summer school I have presented the poster on our FedNL paper.

I have given a talk based on our paper Distributed Second Order Methods with Fast Rates and Compressed Communication at Maths&AI: MIPT-UGA young researchers workshop. The recorded video is available on YouTube. Here you can find the slides that I prepared for the talk.

I am very happy to announce that I defended my Bachelor thesis and finished the undergraduate study at MIPT yesterday. Now I am planning to conitnue my education at Institut Polytechnique de Paris.

We propose a family of Federated Newton Learn (FedNL) methods, which we believe is a marked step in the direction of making second-order methods applicable to FL. We perform a variety of numerical experiments that show that our FedNL methods have state-of-the-art communication complexity when compared to key baselines.