2 citations · 2 across the 2 of their papers we have counts for
4 papers
Distributed Principal Component Analysis with Limited Communication
Foivos Alimisis, Peter Davies, Bart Vandereycken +1
We study efficient distributed algorithms for the fundamental problem of principal component analysis and leading eigenvector computation on the sphere, when the data are randomly…
Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh
We investigate fast and communication-efficient algorithms for the classic problem of minimizing a sum of strongly convex and smooth functions that are distributed among differ…
Momentum Improves Optimization on Riemannian Manifolds
Foivos Alimisis, Antonio Orvieto, Gary Bécigneul +1
We develop a new Riemannian descent algorithm that relies on momentum to improve over existing first-order methods for geodesically convex optimization. In contrast, accelerated co…
A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization
Foivos Alimisis, Antonio Orvieto, Gary Bécigneul +1
We propose a novel second-order ODE as the continuous-time limit of a Riemannian accelerated gradient-based method on a manifold with curvature bounded from below. This ODE can be…