Dmitry Bylinkin

Unlocking the Potential of Weighting Methods in Federated Learning Through Communication Compression

Enhancing Stability of Physics-Informed Neural Network Training Through Saddle-Point Reformulation

Communication-Efficient Federated Learning with Adaptive Number of Participants

Complexity-Separated Schemes for Addressing Structured Heterogeneity in Federated Learning

A Strategy-Agnostic Framework for Partial Participation in Federated Learning

Accelerated Methods with Complexity Separation Under Data Similarity for Federated Learning Problems

A Robust Training Method for Federated Learning with Partial Participation