A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization. - Foivos Alimisis; Antonio Orvieto; Gary Bécigneul; Aurélien Lucchi (AISTATS, 2020)

Momentum Improves Optimization on Riemannian Manifolds. - Foivos Alimisis; Antonio Orvieto; Gary Bécigneul; Aurélien Lucchi (AISTATS, 2021)

Communication-Efficient Distributed Optimization with Quantized Preconditioners. - Foivos Alimisis; Peter Davies 001; Dan Alistarh (ICML, 2021)

Distributed Principal Component Analysis with Limited Communication. - Foivos Alimisis; Peter Davies 001; Bart Vandereycken; Dan Alistarh (NeurIPS, 2021)

A convexity-like structure for polar decomposition with an application to distributed computing. - Foivos Alimisis; Bart Vandereycken (CoRR, 2024)

A preconditioned inverse iteration with an improved convergence guarantee. - Foivos Alimisis; Daniel Kressner; Nian Shao; Bart Vandereycken (CoRR, 2024)

Gradient-Type Subspace Iteration Methods for the Symmetric Eigenvalue Problem. - Foivos Alimisis; Yousef Saad; Bart Vandereycken (SIAM J. Matrix Anal. Appl., 2024)

Geodesic Convexity of the Symmetric Eigenvalue Problem and Convergence of Steepest Descent. - Foivos Alimisis; Bart Vandereycken (J. Optim. Theory Appl., 2024)