Mathematical optimization is an important branch of applied mathematics. Different classes
of optimization problems are categorized based on their problem structures. While there are …

We present a rigorous and comprehensive survey on extensions to the multicriteria setting of
three well-known scalar optimization algorithms. Multiobjective versions of the steepest …

This paper presents a descent direction method for finding extrema of locally Lipschitz
functions defined on Riemannian manifolds. To this end we define a set-valued mapping …

This paper investigates fairness and bias in Canonical Correlation Analysis (CCA), a widely
used statistical technique for examining the relationship between two sets of variables. We …

In this article, we present the proximal point method for finding minima of a special class of
nonconvex function on a Hadamard manifold. The well definedness of the sequence …

This paper presents a Riemannian trust region algorithm for unconstrained optimization
problems with locally Lipschitz objective functions defined on complete Riemannian …

Motivated by Nash equilibrium problems on 'curved'strategy sets, the concept of Nash–
Stampacchia equilibrium points is introduced via variational inequalities on Riemannian …

We present our view of the state of the art in continuous multiobjective programming. After
an introduction we formulate the multiobjective program (MOP) and define the most …

In this paper, we present two inexact scalarization proximal point methods to solve
quasiconvex multiobjective minimization problems on Hadamard manifolds. Under standard …

We extend and analyze the trust region method for solving smooth and unconstrained
multicriteria optimization problems on Riemannian manifolds. At each iteration of this …