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In this paper, we propose a simple acceleration scheme for Riemanniangradient methods by extrapolating iterates on manifolds. We show when theiterates are generated from Riemannian gradient descent method, the acceleratedscheme achieves the optimal convergence rate asymptotically and iscomputationally more favorable than the recently proposed Riemannian Nesterovaccelerated gradient methods. Our experiments verify the practical benefit ofthe novel acceleration strategy.

Riemannian accelerated gradient methods via extrapolation