53 citations · 56 across the 4 of their papers we have counts for
4 papers
Almost-Linear-Time Algorithms for Markov Chains and New Spectral Primitives for Directed Graphs
Michael B. Cohen, Jonathan Kelner, John Peebles +4
In this paper we introduce a notion of spectral approximation for directed graphs. While there are many potential ways one might define approximation for directed graphs, most of t…
Accelerated Methods for Non-Convex Optimization
Yair Carmon, John C. Duchi, Oliver Hinder +1
We present an accelerated gradient method for non-convex optimization problems with Lipschitz continuous first and second derivatives. The method requires time $O(ε^{-7/4} \log(1/…
Subquadratic Submodular Function Minimization
Deeparnab Chakrabarty, Yin Tat Lee, Aaron Sidford +1
Submodular function minimization (SFM) is a fundamental discrete optimization problem which generalizes many well known problems, has applications in various fields, and can be sol…
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More
Michael B. Cohen, Jon Kelner, John Peebles +3
In this paper, we provide faster algorithms for computing various fundamental quantities associated with random walks on a directed graph, including the stationary distribution, pe…