5 papers
A Second-Order Algorithm Based on Affine Scaling Interior-Point Methods for nonlinear Optimisation with bound constraints
Yonggang Pei, Yubing Lin, Mauricio Silva Louzeiro +1
The homogeneous second-order descent method (Zhang et al. 2025, Mathematics of Operations Research) was initially proposed for unconstrained optimisation problems. HSODM shows exce…
A scalable sequential adaptive cubic regularization algorithm for optimization with general equality constraints
Yonggang Pei, Yubing Lin, Shuai Shao +2
The scalable adaptive cubic regularization method (: Dussault et al. in Math. Program. Ser. A 207(1-2): 191-225, 2024) has been recently proposed for unconstrain…
A subdifferential characterization via Busemann functions and applications to DC optimization on Hadamard manifolds
O. P. Ferreira, D. S. Gonçalves, M. S. Louzeiro +2
This paper investigates the properties of Busemann functions on Hadamard manifolds and their use in optimization algorithms in Riemannian settings. We present a new Busemann-based…
A Busemann hybrid projection-proximal point algorithm for optimization problems on Hadamard manifolds
R. DÃaz Millán, O. P. Ferreira, M. S. Louzeiro +1
We study optimization problems on Hadamard manifolds, motivated by recent advances in geometric approaches to optimization on curved spaces, particularly those involving the struct…
A Riemannian AdaGrad-Norm Method
Glaydston de C. Bento, Geovani N. Grapiglia, Mauricio S. Louzeiro +1
We propose a manifold AdaGrad-Norm method (\textsc{MAdaGrad}), which extends the norm version of AdaGrad (AdaGrad-Norm) to Riemannian optimization. In contrast to line-search schem…