We analyze the dynamics of streaming stochastic gradient descent (SGD) i...
There has been increasing demand for establishing privacy-preserving
met...
We consider the problem (P) of fitting n standard Gaussian
random vector...
We give a description of the high-dimensional limit of one-pass single-b...
Stochastic gradient descent (SGD) is a pillar of modern machine learning...
We analyze the dynamics of large batch stochastic gradient descent with
...
We develop a stochastic differential equation, called homogenized SGD, f...
We analyze a class of stochastic gradient algorithms with momentum on a
...
We propose a new framework, inspired by random matrix theory, for analyz...
We present a probabilistic analysis of two Krylov subspace methods for
s...
We show that a nearly square iid random integral matrix is surjective ov...