Accelerated Methods with Compressed Communications for Distributed
Optimization Problems under Data Similarity
Accelerated Methods with Compressed Communications for Distributed
Optimization Problems under Data Similarity
In recent years, as data and problem sizes have increased, distributed learning has become an essential tool for training high-performance models. However, the communication bottleneck, especially for high-dimensional data, is a challenge. Several techniques have been developed to overcome this problem. These include communication compression and implementation of local steps, …