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Hermitian manifold

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Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Nicolas Henri Bernard Flammarion

We consider minimizing a nonconvex, smooth function

f

on a Riemannian manifold

\mathcal{M}

. We show that a perturbed version of Riemannian gradient descent algorithm converges to a second-order stationary point (and hence is able to escape saddle point ...

2019

Hermitian manifold

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A structured prediction approach for robot imitation learning

Continuation Methods For Riemannian Optimization

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

Tensor network investigation of the hard-square model

On The Singular Set In The Thin Obstacle Problem: Higher-Order Blow-Ups And The Very Thin Obstacle Problem

Gaussians on Riemannian Manifolds for Robot Learning and Adaptive Control

Renormalization of quantum field theory on Riemannian manifolds

Escaping from saddle points on Riemannian manifolds

Some regularity results for p-harmonic mappings between Riemannian manifolds

Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

On The Singular Set In The Thin Obstacle Problem: Higher-Order Blow-Ups And The Very Thin Obstacle Problem

A structured prediction approach for robot imitation learning

Continuation Methods For Riemannian Optimization

Some regularity results for p-harmonic mappings between Riemannian manifolds

Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Gaussians on Riemannian Manifolds for Robot Learning and Adaptive Control

Renormalization of quantum field theory on Riemannian manifolds

Escaping from saddle points on Riemannian manifolds

Tensor network investigation of the hard-square model