Image de couverture de livre

A Riemannian AdaGrad-Norm Method

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Bento, Glaydston de C., Grapiglia, Geovani N., Louzeiro, Mauricio S., Zhang, Daoping
Format:	Preprint
Publié:	2025
Sujets:	Optimization and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

An Adaptive Cubic Regularization quasi-Newton Method on Riemannian Manifolds
par: Louzeiro, Mauricio S., et autres
Publié: (2024)

Inexact Newton Methods for Solving Generalized Equations on Riemannian Manifolds
par: Louzeiro, Mauricio S., et autres
Publié: (2023)

Last Iterate Convergence of AdaGrad-Norm for Convex Non-Smooth Optimization
par: Preobrazhenskaia, Margarita, et autres
Publié: (2026)

AdaGrad under Anisotropic Smoothness
par: Liu, Yuxing, et autres
Publié: (2024)

Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed
par: Chezhegov, Savelii, et autres
Publié: (2024)

Revisiting Convergence of AdaGrad with Relaxed Assumptions
par: Hong, Yusu, et autres
Publié: (2024)

AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates
par: Zhang, Minxin, et autres
Publié: (2025)

Riemannian optimization with finite-difference gradient approximations
par: Taminiau, Timothé, et autres
Publié: (2026)

A Finite-Difference Trust-Region Method for Convexly Constrained Smooth Optimization
par: Davar, Dânâ, et autres
Publié: (2025)

A Non-Monotone Line-Search Method for Minimizing Functions with Spurious Local Minima
par: Aminifard, Zohreh, et autres
Publié: (2025)

On the Complexity of Lower-Order Implementations of Higher-Order Methods
par: Doikov, Nikita, et autres
Publié: (2025)

AdaGrad-Diff: A New Version of the Adaptive Gradient Algorithm
par: Bojovic, Matia, et autres
Publié: (2026)

Sub-sampled Trust-Region Methods with Deterministic Worst-Case Complexity Guarantees
par: Goncalves, Max L. N., et autres
Publié: (2025)

Complexity of quadratic penalty methods with adaptive accuracy under a PL condition for the constraints
par: Goyens, Florentin, et autres
Publié: (2026)

Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
par: Rodomanov, Anton, et autres
Publié: (2024)

Modeling AdaGrad, RMSProp, and Adam with Integro-Differential Equations
par: Heredia, Carlos
Publié: (2024)

Fully Adaptive Zeroth-Order Method for Minimizing Functions with Compressible Gradients
par: Grapiglia, Geovani Nunes, et autres
Publié: (2025)

TRFD: A derivative-free trust-region method based on finite differences for composite nonsmooth optimization
par: Davar, Dânâ, et autres
Publié: (2024)

Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad
par: Liu, Zijian
Publié: (2026)

Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
par: Choudhury, Sayantan, et autres
Publié: (2024)

Universal nonmonotone line search method for nonconvex multiobjective optimization problems with convex constraints
par: Pinheiro, Maria Eduarda, et autres
Publié: (2024)

Active-set Newton-MR methods for nonconvex optimization problems with bound constraints
par: Birgin, Ernesto G., et autres
Publié: (2025)

Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization
par: Jiang, Ruichen, et autres
Publié: (2024)

Enhancing finite-difference based derivative-free optimization methods with machine learning
par: Taminiau, Timothé, et autres
Publié: (2025)

Fenchel Duality Theory and A Primal-Dual Algorithm on Riemannian Manifolds
par: Bergmann, Ronny, et autres
Publié: (2019)

AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods
par: Lau, Tim Tsz-Kit, et autres
Publié: (2024)

Stability and convergence analysis of AdaGrad for non-convex optimization via novel stopping time-based techniques
par: Jin, Ruinan, et autres
Publié: (2024)

Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization
par: Gratton, Serge, et autres
Publié: (2025)

AdaBatchGrad: Combining Adaptive Batch Size and Adaptive Step Size
par: Ostroukhov, Petr, et autres
Publié: (2024)

A scalable sequential adaptive cubic regularization algorithm for optimization with general equality constraints
par: Pei, Yonggang, et autres
Publié: (2025)

Convergence Rates for the Alternating Minimization Algorithm in Structured Nonsmooth and Nonconvex Optimization
par: Bento, Glaydston C., et autres
Publié: (2026)

A Riemannian Proximal Newton Method
par: Si, Wutao, et autres
Publié: (2023)

A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation
par: Boursier, Etienne, et autres
Publié: (2025)

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

AdaBB: Adaptive Barzilai-Borwein Method for Convex Optimization
par: Zhou, Danqing, et autres
Publié: (2024)

A Riemannian Proximal Newton-CG Method
par: Huang, Wen, et autres
Publié: (2024)

A Second-Order Algorithm Based on Affine Scaling Interior-Point Methods for nonlinear Optimisation with bound constraints
par: Pei, Yonggang, et autres
Publié: (2026)

On the Oracle Complexity of a Riemannian Inexact Augmented Lagrangian Method for Riemannian Nonsmooth Composite Problems
par: Xu, Meng, et autres
Publié: (2024)

Stochastic Augmented Lagrangian Method in Riemannian Shape Manifolds
par: Geiersbach, Caroline, et autres
Publié: (2023)

An Invitation to Higher-Order Riemannian Optimization: Optimal and Implementable Methods
par: Gutman, David Huckleberry, et autres
Publié: (2026)