Stochastic nested optimization, including stochastic compositional, min-...
Stochastic bilevel optimization generalizes the classic stochastic
optim...
Stochastic gradient descent (SGD) has taken the stage as the primary
wor...
Stochastic compositional optimization generalizes classic (non-compositi...
Horizontal Federated learning (FL) handles multi-client data that share ...
This paper targets solving distributed machine learning problems such as...
The incremental aggregated gradient algorithm is popular in network
opti...
Decentralized stochastic gradient method emerges as a promising solution...
The method of block coordinate gradient descent (BCD) has been a powerfu...
Stochastic gradient methods are the workhorse (algorithms) of large-scal...