12 citations · 12 across the 1 of their papers we have counts for
4 papers
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method
Yossi Arjevani, Joan Bruna, Bugra Can +3
We introduce a framework for designing primal methods under the decentralized optimization setting where local functions are smooth and strongly convex. Our approach consists of ap…
Conditional Law and Occupation Times of Two-Sided Sticky Brownian Motion
Bugra Can, Mine Caglar
Sticky Brownian motion on the real line can be obtained as a weak solution of a system of stochastic differential equations. We find the conditional distribution of the process giv…
ASYNC: A Cloud Engine with Asynchrony and History for Distributed Machine Learning
Saeed Soori, Bugra Can, Mert Gurbuzbalaba +1
ASYNC is a framework that supports the implementation of asynchrony and history for optimization methods on distributed computing platforms. The popularity of asynchronous optimiza…
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
Bugra Can, Mert Gurbuzbalaban, Lingjiong Zhu
Momentum methods such as Polyak's heavy ball (HB) method, Nesterov's accelerated gradient (AG) as well as accelerated projected gradient (APG) method have been commonly used in mac…