Cover Image

On Busemann subgradient methods for stochastic minimization in Hadamard spaces

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Pischke, Nicholas
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the proximal point algorithm for strongly quasiconvex functions in Hadamard spaces
by: Pischke, Nicholas
Published: (2024)

Weak convergence of the stochastic proximal point method in metric spaces
by: Pischke, Nicholas
Published: (2026)

Mean-square and linear convergence of a stochastic proximal point algorithm in metric spaces of nonpositive curvature
by: Pischke, Nicholas
Published: (2025)

Convergence guarantees for stochastic algorithms solving non-unique problems in metric spaces
by: Pischke, Nicholas, et al.
Published: (2026)

Asymptotic regularity of a generalised stochastic Halpern scheme
by: Pischke, Nicholas, et al.
Published: (2024)

Generalized fluctuation bounds for stochastic algorithms in the presence of compactness
by: Neri, Morenikeji, et al.
Published: (2026)

An abstract effective convergence theorem for stochastic processes, with applications to stochastic approximation
by: Neri, Morenikeji, et al.
Published: (2025)

A subdifferential characterization via Busemann functions and applications to DC optimization on Hadamard manifolds
by: Ferreira, O. P., et al.
Published: (2026)

Mini-batch stochastic subgradient for functional constrained optimization
by: Singh, Nitesh Kumar, et al.
Published: (2024)

Effective rates for continuous-time quasi-Fejér monotone dynamical systems
by: Freund, Anton, et al.
Published: (2026)

Stochastic and incremental subgradient methods for convex optimization on Hadamard spaces
by: Goodwin, Ariel, et al.
Published: (2024)

Inexact subgradient methods for semialgebraic functions
by: Bolte, Jérôme, et al.
Published: (2024)

Exact Convergence rate of the subgradient method by using Polyak step size
by: Zamani, Moslem, et al.
Published: (2024)

On the diameter of subgradient sequences in o-minimal structures
by: Lai, Lexiao, et al.
Published: (2025)

Universal subgradient and proximal bundle methods for convex and strongly convex hybrid composite optimization
by: Guigues, Vincent, et al.
Published: (2024)

Stochastic subgradient for composite optimization with functional constraints
by: Necoara, Ion, et al.
Published: (2022)

A self-adaptive subgradient extragradient method with conjugate gradient-type direction for pseudomonotone variational inequalities
by: Arzuka, Ibrahim, et al.
Published: (2025)

Hybrid subgradient and simulated annealing method for hemivariational inequalities
by: Bartman-Szwarc, Piotr, et al.
Published: (2025)

Random minibatch subgradient algorithms for convex problems with functional constraints
by: Nedich, Angelia, et al.
Published: (2019)

A single-loop SPIDER-type stochastic subgradient method for expectation-constrained nonconvex nonsmooth optimization
by: Liu, Wei, et al.
Published: (2025)

A stochastic perturbed augmented Lagrangian method for smooth convex constrained minimization
by: Singh, Nitesh Kumar, et al.
Published: (2025)

A stochastic moving ball approximation method for smooth convex constrained minimization
by: Singh, Nitesh Kumar, et al.
Published: (2024)

A proximal subgradient algorithm for constrained multiobjective DC-type optimization
by: Van Tuyen, Nguyen, et al.
Published: (2025)

The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks
by: Schechtman, Sholom, et al.
Published: (2025)

Convergence of empirical subgradients for optimal transport-based objectives
by: Le, Tam
Published: (2026)

An effective subgradient algorithm via Mifflin's line search for nonsmooth nonconvex multiobjective optimization
by: Maleknia, Morteza, et al.
Published: (2024)

Inexact subgradient algorithm with a non-asymptotic convergence guarantee for copositive programming problems
by: Nishijima, Mitsuhiro, et al.
Published: (2025)

On convergence rates of subgradient descent on semialgebraic functions
by: Chzhen, Evgenii, et al.
Published: (2026)

An Inexact Variable Metric Proximal Gradient-subgradient Algorithm for a Class of Fractional Optimization Problems
by: Yang, Lei, et al.
Published: (2025)

A nonmonotone extrapolated proximal gradient-subgradient algorithm beyond global Lipschitz gradient continuity
by: Yang, Lei, et al.
Published: (2025)

Computing AD-compatible subgradients of convex relaxations of implicit functions
by: Song, Yingkai, et al.
Published: (2025)

Convergence analysis of stochastic higher-order majorization-minimization algorithms
by: Lupu, Daniela, et al.
Published: (2021)

Horoballs and the subgradient method
by: Lewis, Adrian S., et al.
Published: (2024)

A multilevel stochastic regularized first-order method with application to finite sum minimization
by: Marini, Filippo, et al.
Published: (2024)

Global convergence of the subgradient method for robust signal recovery
by: Cai, Zesheng, et al.
Published: (2026)

The proximal point method and its two variants for monotone vector fields in Hadamard spaces
by: Chaipunya, Parin, et al.
Published: (2026)

Multi-cut stochastic approximation methods for solving stochastic convex composite optimization
by: Liang, Jiaming, et al.
Published: (2025)

A Busemann hybrid projection-proximal point algorithm for optimization problems on Hadamard manifolds
by: Millán, R. Díaz, et al.
Published: (2026)

Computer-aided analyses of stochastic first-order methods, via interpolation conditions for stochastic optimization
by: Rubbens, Anne, et al.
Published: (2025)

Almost sure convergence of stochastic Hamiltonian descent methods
by: Williamson, Måns, et al.
Published: (2024)