A Riemannian View on Shape Optimization

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Riemannian View on Shape Optimization

Shape optimization based on the shape calculus is numerically mostly performed by means of steepest descent methods. This paper provides a novel framework to analyze shapeNewton optimization methods by exploiting a Riemannian perspective. A Riemannian shape Hessian is defined yielding often sought properties like symmetry and quadratic convergence for Newton optimization methods.

متن کامل

Riemannian Optimization for Elastic Shape Analysis

In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotation and reparameterization and important problems (such as computing the distance and geodesic between two curves, the mean of a set of curves, and other statistical analyses) require finding a best rotation and re-parameterization between two curves. In this paper, we focus on this key subproblem ...

متن کامل

Optimization Techniques on Riemannian Manifolds

The techniques and analysis presented in this paper provide new methods to solve optimization problems posed on Riemannian manifolds. A new point of view is offered for the solution of constrained optimization problems. Some classical optimization techniques on Euclidean space are generalized to Riemannian manifolds. Several algorithms are presented and their convergence properties are analyzed...

متن کامل

Riemannian Shape Analysis

This paper will introduce a new way to compare parameterized surfaces using Riemannian shape analysis. To represent those surfaces, a form of q-maps will be developed which allow to define a special metric of functions that is invariant to rigid motion, global scaling and re-parametrization of the surfaces. This metric leads to the definition of the Riemannian distance function, which minimizes...

متن کامل

Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds

We study optimization of finite sums of geodesically smooth functions on Riemannian manifolds. Although variance reduction techniques for optimizing finite-sums have witnessed tremendous attention in the recent years, existing work is limited to vector space problems. We introduce Riemannian SVRG (RSVRG), a new variance reduced Riemannian optimization method. We analyze RSVRG for both geodesica...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Foundations of Computational Mathematics

سال: 2014

ISSN: 1615-3375,1615-3383

DOI: 10.1007/s10208-014-9200-5