We propose an adaptive variance-reduction method, called AdaSpider, for
...
This work proposes a universal and adaptive second-order method for
mini...
In this paper, we propose a new, simplified high probability analysis of...
In this work we investigate stochastic non-convex optimization problems ...
A well-known first-order method for sampling from log-concave probabilit...
This paper analyzes the trajectories of stochastic gradient descent (SGD...
We propose a novel adaptive, accelerated algorithm for the stochastic
co...
We study the fundamental problem of learning an unknown, smooth probabil...