Image de couverture de livre

Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kim, Jungbin, Yang, Insoon
Format:	Preprint
Publié:	2022
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

A Proof of the Exact Convergence Rate of Gradient Descent
par: Kim, Jungbin
Publié: (2024)

Horospherically Convex Optimization on Hadamard Manifolds Part I: Analysis and Algorithms
par: Criscitiello, Christopher, et autres
Publié: (2025)

A Proof of Exact Convergence Rate of Gradient Descent. Part I. Performance Criterion $\Vert \nabla f(x_N)\Vert^2/(f(x_0)-f_*)$
par: Kim, Jungbin
Publié: (2024)

Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods
par: Park, Chanwoong, et autres
Publié: (2024)

Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity
par: Zhu, Shuailong, et autres
Publié: (2025)

Adaptive Accelerated Gradient Method for Smooth Convex Optimization
par: Wang, Zepeng, et autres
Publié: (2025)

Adaptive Accelerated Gradient Descent Methods for Convex Optimization
par: Xu, Zeyi, et autres
Publié: (2026)

Deterministic and Stochastic Accelerated Gradient Method for Convex Semi-Infinite Optimization
par: Yao, Yao, et autres
Publié: (2023)

Convergence Analysis of Stochastic Accelerated Gradient Methods for Generalized Smooth Optimizations
par: Yu, Chenhao, et autres
Publié: (2025)

Revisit First-order Methods for Geodesically Convex Optimization
par: Shu, Yunlu, et autres
Publié: (2025)

Point Convergence Analysis of the Accelerated Gradient Method for Multiobjective Optimization: Continuous and Discrete
par: Yin, Yingdong
Publié: (2025)

An Adaptive and Parameter-Free Nesterov's Accelerated Gradient Method for Convex Optimization
par: Suh, Jaewook J., et autres
Publié: (2025)

Convergence Rate Analysis for Monotone Accelerated Proximal Gradient Method
par: Wang, Zepeng, et autres
Publié: (2025)

Restart-Free (Accelerated) Gradient Sliding Methods for Strongly Convex Composite Optimization
par: Wu, Xinming, et autres
Publié: (2026)

An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization
par: Cao, Jincheng, et autres
Publié: (2024)

Technical Report: A Totally Asynchronous Nesterov's Accelerated Gradient Method for Convex Optimization
par: Pond, Ellie, et autres
Publié: (2024)

Tight Analysis of Difference-of-Convex Algorithm (DCA) Improves Convergence Rates for Proximal Gradient Descent
par: Rotaru, Teodor, et autres
Publié: (2025)

HNAG$^{++}$: An Accelerated Gradient Method with a Refined Asymptotic Rate for Strongly Convex Optimization
par: Chen, Long, et autres
Publié: (2025)

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization
par: Liu, Zijian, et autres
Publié: (2025)

Universal Gradient Methods for Stochastic Convex Optimization
par: Rodomanov, Anton, et autres
Publié: (2024)

Accelerated Backward Forward Method for Convex Optimization
par: Wang, Zepeng, et autres
Publié: (2026)

Tight Convergence Rates in Gradient Mapping for the Difference-of-Convex Algorithm
par: Rotaru, Teodor, et autres
Publié: (2025)

Exponential Convergence of Augmented Primal-dual Gradient Algorithms for Partially Strongly Convex Functions
par: Li, Mengmou, et autres
Publié: (2024)

Distributed Adaptive Gradient Algorithm with Gradient Tracking for Stochastic Non-Convex Optimization
par: Han, Dongyu, et autres
Publié: (2024)

Smoothing Accelerated Proximal Gradient Method with Fast Convergence Rate for Nonsmooth Multi-objective Optimization
par: Huang, Chengzhi
Publié: (2023)

On Tractability, Complexity, and Mixed-Integer Convex Programming Representability of Distributionally Favorable Optimization
par: Jiang, Nan, et autres
Publié: (2024)

Shuffling Momentum Gradient Algorithm for Convex Optimization
par: Tran, Trang H., et autres
Publié: (2024)

Faster Newton Methods for Convex and Nonconvex Optimization in Gradient Complexity
par: Chen, Lesi, et autres
Publié: (2025)

Distributed and Inexact Proximal Gradient Method for Online Convex Optimization
par: Bastianello, Nicola, et autres
Publié: (2020)

Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
par: Zhang, Liang, et autres
Publié: (2023)

Convergence Analysis of the PAGE Stochastic Algorithm for Weakly Convex Finite-Sum Optimization
par: Condat, Laurent, et autres
Publié: (2025)

Point Convergence of Nesterov's Accelerated Gradient Method: An AI-Assisted Proof
par: Jang, Uijeong, et autres
Publié: (2025)

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
par: Zhou, Dongruo, et autres
Publié: (2018)

First Order Algorithm on an Optimization Problem with Improved Convergence when Problem is Convex
par: Sim, Chee-Khian
Publié: (2025)

Accelerated Distance-adaptive Methods for Hölder Smooth and Convex Optimization
par: Ren, Yijin, et autres
Publié: (2025)

Wasserstein Distributionally Robust Control and State Estimation for Partially Observable Linear Systems
par: Jang, Minhyuk, et autres
Publié: (2024)

Robust Continuous-Time Generation Scheduling under Power Demand Uncertainty: An Affine Decision Rule Approach
par: Cho, Youngchae, et autres
Publié: (2025)

Distributionally Robust Kalman Filter
par: Jang, Minhyuk, et autres
Publié: (2025)

Complexity of Projected Gradient Methods for Strongly Convex Optimization with Hölder Continuous Gradient Terms
par: Chen, Xiaojun, et autres
Publié: (2026)

Learning Acceleration Algorithms for Fast Parametric Convex Optimization with Certified Robustness
par: Sambharya, Rajiv, et autres
Publié: (2025)