Last-Iterate Convergence of Anchored Gradient Descent
Fuente:
arXiv
Saved in:
| Main Authors: | Cai, Yang, Zheng, Weiqiang |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Improved Last-Iterate Convergence Rate for Anchored Gradient Descent Ascent
by: Surina, Anja, et al.
Published: (2026)
by: Surina, Anja, et al.
Published: (2026)
Last-Iterate Convergence of Adaptive Riemannian Gradient Descent for Equilibrium Computation
by: Cai, Yang, et al.
Published: (2023)
by: Cai, Yang, et al.
Published: (2023)
From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications
by: Cai, Yang, et al.
Published: (2025)
by: Cai, Yang, et al.
Published: (2025)
On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer
by: Chakrabarti, Kushal, et al.
Published: (2024)
by: Chakrabarti, Kushal, et al.
Published: (2024)
Gradient Descent's Last Iterate is Often (slightly) Suboptimal
by: Kornowski, Guy, et al.
Published: (2026)
by: Kornowski, Guy, et al.
Published: (2026)
On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
by: Cai, Yang, et al.
Published: (2025)
by: Cai, Yang, et al.
Published: (2025)
Convergence Analysis of the Last Iterate in Distributed Stochastic Gradient Descent with Momentum
by: Cheng, Difei, et al.
Published: (2025)
by: Cheng, Difei, et al.
Published: (2025)
On the Last-Iterate Convergence of Shuffling Gradient Methods
by: Liu, Zijian, et al.
Published: (2024)
by: Liu, Zijian, et al.
Published: (2024)
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
by: Liu, Zijian, et al.
Published: (2023)
by: Liu, Zijian, et al.
Published: (2023)
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
by: Cai, Yang, et al.
Published: (2024)
by: Cai, Yang, et al.
Published: (2024)
Convergence Rate for the Last Iterate of Stochastic Gradient Descent Schemes
by: Hudiani, Marcel
Published: (2025)
by: Hudiani, Marcel
Published: (2025)
Last Iterate Convergence of Incremental Methods and Applications in Continual Learning
by: Cai, Xufeng, et al.
Published: (2024)
by: Cai, Xufeng, et al.
Published: (2024)
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2023)
by: Ding, Dongsheng, et al.
Published: (2023)
Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization
by: Liu, Zijian, et al.
Published: (2025)
by: Liu, Zijian, et al.
Published: (2025)
A Proof of the Exact Convergence Rate of Gradient Descent
by: Kim, Jungbin
Published: (2024)
by: Kim, Jungbin
Published: (2024)
Convergence of the Iterates of the Stochastic Proximal Gradient Method
by: Madariaga, Javier I.
Published: (2026)
by: Madariaga, Javier I.
Published: (2026)
Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
by: Vaidyan, Kevin Kurian Thomas, et al.
Published: (2026)
by: Vaidyan, Kevin Kurian Thomas, et al.
Published: (2026)
Last Iterate Convergence of AdaGrad-Norm for Convex Non-Smooth Optimization
by: Preobrazhenskaia, Margarita, et al.
Published: (2026)
by: Preobrazhenskaia, Margarita, et al.
Published: (2026)
Last Iterate Convergence of Popov Method for Non-monotone Stochastic Variational Inequalities
by: Vankov, Daniil, et al.
Published: (2023)
by: Vankov, Daniil, et al.
Published: (2023)
High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise
by: Yang, Yuchen, et al.
Published: (2025)
by: Yang, Yuchen, et al.
Published: (2025)
Accelerated Objective Gap and Gradient Norm Convergence for Gradient Descent via Long Steps
by: Grimmer, Benjamin, et al.
Published: (2024)
by: Grimmer, Benjamin, et al.
Published: (2024)
Learning Provably Improves the Convergence of Gradient Descent
by: Song, Qingyu, et al.
Published: (2025)
by: Song, Qingyu, et al.
Published: (2025)
Convergence of Alternating Gradient Descent for Matrix Factorization
by: Ward, Rachel, et al.
Published: (2023)
by: Ward, Rachel, et al.
Published: (2023)
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point
by: Martínez-Rubio, David, et al.
Published: (2024)
by: Martínez-Rubio, David, et al.
Published: (2024)
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
by: Attia, Amit, et al.
Published: (2025)
by: Attia, Amit, et al.
Published: (2025)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023)
by: Li, Tianyou, et al.
Published: (2023)
Open Problem: Anytime Convergence Rate of Gradient Descent
by: Kornowski, Guy, et al.
Published: (2024)
by: Kornowski, Guy, et al.
Published: (2024)
On the Convergence of Gradient Descent on Learning Transformers with Residual Connections
by: Qin, Zhen, et al.
Published: (2025)
by: Qin, Zhen, et al.
Published: (2025)
Convergence of First-Order Algorithms with Momentum from the Perspective of an Inexact Gradient Descent Method
by: Khanh, Pham Duy, et al.
Published: (2025)
by: Khanh, Pham Duy, et al.
Published: (2025)
The Anytime Convergence of Stochastic Gradient Descent with Momentum: From a Continuous-Time Perspective
by: Feng, Yasong, et al.
Published: (2023)
by: Feng, Yasong, et al.
Published: (2023)
Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
by: Kale, Sacchit, et al.
Published: (2026)
by: Kale, Sacchit, et al.
Published: (2026)
On the Convergence of Stochastic Gradient Descent with Perturbed Forward-Backward Passes
by: Kong, Boao, et al.
Published: (2026)
by: Kong, Boao, et al.
Published: (2026)
Convergence Properties of Natural Gradient Descent for Minimizing KL Divergence
by: Datar, Adwait, et al.
Published: (2025)
by: Datar, Adwait, et al.
Published: (2025)
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
by: Mishkin, Aaron, et al.
Published: (2024)
by: Mishkin, Aaron, et al.
Published: (2024)
Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion
by: Ma, Jianhao, et al.
Published: (2024)
by: Ma, Jianhao, et al.
Published: (2024)
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
by: Jung, Hyunji, et al.
Published: (2025)
by: Jung, Hyunji, et al.
Published: (2025)
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
by: Zheng, Yuping, et al.
Published: (2025)
by: Zheng, Yuping, et al.
Published: (2025)
Tight Analysis of Difference-of-Convex Algorithm (DCA) Improves Convergence Rates for Proximal Gradient Descent
by: Rotaru, Teodor, et al.
Published: (2025)
by: Rotaru, Teodor, et al.
Published: (2025)
Convergence Analysis of Noisy Distributed Gradient Descent for Non-convex Optimization -- Saddle Point Escape
by: Qin, Lei, et al.
Published: (2025)
by: Qin, Lei, et al.
Published: (2025)
High Probability Convergence Bounds for Non-convex Stochastic Gradient Descent with Sub-Weibull Noise
by: Madden, Liam, et al.
Published: (2020)
by: Madden, Liam, et al.
Published: (2020)
Similar Items
-
An Improved Last-Iterate Convergence Rate for Anchored Gradient Descent Ascent
by: Surina, Anja, et al.
Published: (2026) -
Last-Iterate Convergence of Adaptive Riemannian Gradient Descent for Equilibrium Computation
by: Cai, Yang, et al.
Published: (2023) -
From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications
by: Cai, Yang, et al.
Published: (2025) -
On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer
by: Chakrabarti, Kushal, et al.
Published: (2024) -
Gradient Descent's Last Iterate is Often (slightly) Suboptimal
by: Kornowski, Guy, et al.
Published: (2026)