Nonsmooth Riemannian optimization is a still scarcely explored subfield of optimization theory that concerns the general problem of minimizing (or maximizing), over a domain endowed with a manifold structure, a real-valued function that is not everywhere differentiable. The purpose of this paper is to illustrate, by means of nine concrete examples, that nonsmooth Riemannian optimization finds numerous applications in engineering and the sciences
Nonsmooth optimisation problems are problems which deal with minimisation or maximisation of functio...
Abstract. The subgradient method is generalized to the context of Riemannian manifolds. The motivati...
Nonconvex Optimization is a multi-disciplinary research field that deals with the characterization a...
This book deals with nonsmooth structures arising within the optimization setting. It considers four...
International audienceOptimisation algorithms such as the Newton method were first generalised to ma...
Nonsmoothness in optimization is typically highly structured, and this structure is fundamental to a...
The main goal of our study is an attempt to understand and classify nonsmooth structures arising wit...
Since nonsmooth optimization problems arise in a diverse range of real-world applications, the poten...
Summary. This paper provides an introduction to the topic of optimization on manifolds. The approach...
ness in analysis and optimization, which is of course not new, but to the attempts to consider diffe...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
How to make the best decision? This general concern, pervasive in both research and industry, is wha...
Numerical minimisation of a cost function on Euclidean space is a well studied problem. Sometimes th...
Abstract. This paper develops and analyzes a generalization of the Broyden class of quasi-Newton met...
This paper provides an introduction to the topic of optimization on manifolds. The approach taken u...
Nonsmooth optimisation problems are problems which deal with minimisation or maximisation of functio...
Abstract. The subgradient method is generalized to the context of Riemannian manifolds. The motivati...
Nonconvex Optimization is a multi-disciplinary research field that deals with the characterization a...
This book deals with nonsmooth structures arising within the optimization setting. It considers four...
International audienceOptimisation algorithms such as the Newton method were first generalised to ma...
Nonsmoothness in optimization is typically highly structured, and this structure is fundamental to a...
The main goal of our study is an attempt to understand and classify nonsmooth structures arising wit...
Since nonsmooth optimization problems arise in a diverse range of real-world applications, the poten...
Summary. This paper provides an introduction to the topic of optimization on manifolds. The approach...
ness in analysis and optimization, which is of course not new, but to the attempts to consider diffe...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
How to make the best decision? This general concern, pervasive in both research and industry, is wha...
Numerical minimisation of a cost function on Euclidean space is a well studied problem. Sometimes th...
Abstract. This paper develops and analyzes a generalization of the Broyden class of quasi-Newton met...
This paper provides an introduction to the topic of optimization on manifolds. The approach taken u...
Nonsmooth optimisation problems are problems which deal with minimisation or maximisation of functio...
Abstract. The subgradient method is generalized to the context of Riemannian manifolds. The motivati...
Nonconvex Optimization is a multi-disciplinary research field that deals with the characterization a...