Abstract. Bearing in mind the notion of monotone vector field on Riemannian manifolds, see [12–16], we study the set of their singularities and for a particular class of manifolds develop an extragradient-type algorithm convergent to singularities of such vector fields. In particular, our method can be used for solving nonlinear constrained optimization problems in Euclidean space, with a convex objective function and the constraint set a constant curvature Hadamard manifold. Our paper shows how tools of convex analysis on Riemannian manifolds can be used to solve some nonconvex constrained problem in a Euclidean space
Abstract. The subgradient method is generalized to the context of Riemannian manifolds. The motivati...
This unique monograph discusses the interaction between Riemannian geometry, convex programming, num...
International audienceWe propose an inertial proximal point method for variational inclusion involvi...
Abstract. The problem of finding the singularities of monotone vectors fields on Hadamard manifolds ...
The relationship between monotonicity and accretivity on Riemannian manifolds is studied in this pap...
This paper briefly surveys some recent advances in the investigation of nonexpansive mappings and mo...
This paper presents an extragradient method for variational inequality associated with a point-to-se...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
In this paper, we propose a class of constraint dissolving approaches for optimization problems over...
In this thesis, we present an inexact proximal point algorithm to solve quasiconvex optimization pro...
A quasi-Riemannian approach is developed for constrained optimization in which the retraction and tr...
In this paper we propose an extension of the proximal point method to solve minimization problems wi...
Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combine...
In this paper we consider the minimization problem with constraints. We will show that if the set of...
Real-life problems are governed by equations which are nonlinear in nature. Nonlinear equations occu...
Abstract. The subgradient method is generalized to the context of Riemannian manifolds. The motivati...
This unique monograph discusses the interaction between Riemannian geometry, convex programming, num...
International audienceWe propose an inertial proximal point method for variational inclusion involvi...
Abstract. The problem of finding the singularities of monotone vectors fields on Hadamard manifolds ...
The relationship between monotonicity and accretivity on Riemannian manifolds is studied in this pap...
This paper briefly surveys some recent advances in the investigation of nonexpansive mappings and mo...
This paper presents an extragradient method for variational inequality associated with a point-to-se...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
In this paper, we propose a class of constraint dissolving approaches for optimization problems over...
In this thesis, we present an inexact proximal point algorithm to solve quasiconvex optimization pro...
A quasi-Riemannian approach is developed for constrained optimization in which the retraction and tr...
In this paper we propose an extension of the proximal point method to solve minimization problems wi...
Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combine...
In this paper we consider the minimization problem with constraints. We will show that if the set of...
Real-life problems are governed by equations which are nonlinear in nature. Nonlinear equations occu...
Abstract. The subgradient method is generalized to the context of Riemannian manifolds. The motivati...
This unique monograph discusses the interaction between Riemannian geometry, convex programming, num...
International audienceWe propose an inertial proximal point method for variational inclusion involvi...