9 citations · 10 across the 3 of their papers we have counts for
3 papers
Enhancing Stability of Physics-Informed Neural Network Training Through Saddle-Point Reformulation
Dmitry Bylinkin, Mikhail Aleksandrov, Savelii Chezhegov +1
Physics-informed neural networks (PINNs) have gained prominence in recent years and are now effectively used in a number of applications. However, their performance remains unstabl…
Local Methods with Adaptivity via Scaling
Savelii Chezhegov, Sergey Skorik, Nikolas Khachaturov +5
The rapid development of machine learning and deep learning has introduced increasingly complex optimization challenges that must be addressed. Indeed, training modern, advanced mo…
Decentralized Personalized Federated Learning: Lower Bounds and Optimal Algorithm for All Personalization Modes
Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov +5
This paper considers the problem of decentralized, personalized federated learning. For centralized personalized federated learning, a penalty that measures the deviation from the…