In addition to recent developments in computing speed and memory, methodological advances have contributed significant gains the performance of stochastic simulation. this paper, we focus on variance reduction for matrix computations via factorization. We provide insights into existing methods estimating entries large matrices. Popular do not exploit that is possible when factorized. show how s...

We consider distributed optimization over several devices, each sending incremental model updates to a central server. This setting is considered, for instance, in federated learning. Various schemes have been designed compress the order reduce overall communication cost. However, existing methods suffer from significant slowdown due additional variance ?>0 coming compression operator and as re...