In this paper, we study the stochastic linear bandit problem under the
a...
We develop an eigenspace estimation algorithm for distributed environmen...
Distributed computing is a standard way to scale up machine learning and...
Several problems in machine learning, statistics, and other fields rely ...
Several fundamental tasks in data science rely on computing an extremal
...
Stochastic (sub)gradient methods require step size schedule tuning to pe...
The task of recovering a low-rank matrix from its noisy linear measureme...
The blind deconvolution problem seeks to recover a pair of vectors from ...
We present a new, unifying approach following some recent developments o...