8 citations · 42 across the 23 of their papers we have counts for
5 papers · 1 filter
Differentially private Riemannian optimization
Andi Han, Bamdev Mishra, Pratik Jawanpuria +1
In this paper, we study the differentially private empirical risk minimization problem where the parameter is constrained to a Riemannian manifold. We introduce a framework of diff…
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry
Andi Han, Bamdev Mishra, Pratik Jawanpuria +1
In this paper, we comparatively analyze the Bures-Wasserstein (BW) geometry with the popular Affine-Invariant (AI) geometry for Riemannian optimization on the symmetric positive de…
Escape saddle points faster on manifolds via perturbed Riemannian stochastic recursive gradient
Andi Han, Junbin Gao
In this paper, we propose a variant of Riemannian stochastic recursive gradient method that can achieve second-order convergence guarantee and escape saddle points using simple per…
Riemannian stochastic recursive momentum method for non-convex optimization
Andi Han, Junbin Gao
We propose a stochastic recursive momentum method for Riemannian non-convex optimization that achieves a near-optimal complexity of to find -approx…
Variance reduction for Riemannian non-convex optimization with batch size adaptation
Andi Han, Junbin Gao
Variance reduction techniques are popular in accelerating gradient descent and stochastic gradient descent for optimization problems defined on both Euclidean space and Riemannian…