most citedUnifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond

4 citations · 6 across the 3 of their papers we have counts for

collaborators
Showing math.OCShow all

2 papers · 1 filter

math.OC2024

Riemannian coordinate descent algorithms on matrix manifolds

Andi Han, Pratik Jawanpuria, Bamdev Mishra

Many machine learning applications are naturally formulated as optimization problems on Riemannian manifolds. The main idea behind Riemannian optimization is to maintain the feasib…

math.OC2022

Riemannian accelerated gradient methods via extrapolation

Andi Han, Bamdev Mishra, Pratik Jawanpuria +1

In this paper, we propose a simple acceleration scheme for Riemannian gradient methods by extrapolating iterates on manifolds. We show when the iterates are generated from Riemanni…