In this paper, we provide a novel framework for the analysis of
generali...
We study a variation of vanilla stochastic gradient descent where the
op...
In this paper, we investigate the impact of stochasticity and large step...
The existing analysis of asynchronous stochastic gradient descent (SGD)
...
Decentralized optimization is increasingly popular in machine learning f...
We introduce the continuized Nesterov acceleration, a close variant of
N...
In decentralized optimization, nodes of a communication network privatel...
Dimension is an inherent bottleneck to some modern learning tasks, where...
This paper considers the minimization of a sum of smooth and strongly co...