Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Fuente:
arXiv
Saved in:
| Main Authors: | Peng, Liangzu, Yin, Wotao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Projected Block Coordinate Descent for sparse spike estimation
by: Bénard, Pierre-Jean, et al.
Published: (2024)
by: Bénard, Pierre-Jean, et al.
Published: (2024)
Scaled Relative Graph of Normal Matrices
by: Huang, Xinmeng, et al.
Published: (2019)
by: Huang, Xinmeng, et al.
Published: (2019)
Dual Block Gradient Ascent for Entropically Regularised Quantum Optimal Transport
by: Randig, Marvin, et al.
Published: (2025)
by: Randig, Marvin, et al.
Published: (2025)
Modified Loss of Momentum Gradient Descent: Fine-Grained Analysis
by: Cattaneo, Matias D., et al.
Published: (2025)
by: Cattaneo, Matias D., et al.
Published: (2025)
A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
by: Yuan, Ganzhao
Published: (2023)
by: Yuan, Ganzhao
Published: (2023)
Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty
by: Baumgarten, Niklas, et al.
Published: (2025)
by: Baumgarten, Niklas, et al.
Published: (2025)
Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration
by: Tyurin, Alexander
Published: (2025)
by: Tyurin, Alexander
Published: (2025)
Low-Discrepancy Set Post-Processing via Gradient Descent
by: Clément, François, et al.
Published: (2025)
by: Clément, François, et al.
Published: (2025)
IRKA is a Riemannian Gradient Descent Method
by: Mlinarić, Petar, et al.
Published: (2023)
by: Mlinarić, Petar, et al.
Published: (2023)
Block Matrix and Tensor Randomized Kaczmarz Methods for Linear Feasibility Problems
by: Zhang, Minxin, et al.
Published: (2024)
by: Zhang, Minxin, et al.
Published: (2024)
The Dynamical Anatomy of Anderson Acceleration:From Adaptive Momentum to Variable-Mass ODEs
by: Chen, Kewang, et al.
Published: (2025)
by: Chen, Kewang, et al.
Published: (2025)
Block triangular preconditioning for elliptic boundary optimal control with mixed boundary conditions
by: Wang, Chaojie
Published: (2024)
by: Wang, Chaojie
Published: (2024)
The Essential Best and Average Rate of Convergence of the Exact Line Search Gradient Descent Method
by: Yu, Thomas
Published: (2023)
by: Yu, Thomas
Published: (2023)
Policy Gradient with Second Order Momentum
by: Sun, Tianyu
Published: (2025)
by: Sun, Tianyu
Published: (2025)
Super Gradient Descent: Global Optimization requires Global Gradient
by: Achour, Seifeddine
Published: (2024)
by: Achour, Seifeddine
Published: (2024)
Provably Faster Gradient Descent via Long Steps
by: Grimmer, Benjamin
Published: (2023)
by: Grimmer, Benjamin
Published: (2023)
Accelerated Primal-Dual Proximal Gradient Splitting Methods for Convex-Concave Saddle-Point Problems
by: Luo, Hao
Published: (2024)
by: Luo, Hao
Published: (2024)
SVD-Preconditioned Gradient Descent Method for Solving Nonlinear Least Squares Problems
by: Chang, Zhipeng, et al.
Published: (2026)
by: Chang, Zhipeng, et al.
Published: (2026)
A Family of Controllable Momentum Coefficients for Forward-Backward Accelerated Algorithms
by: Fu, Mingwei, et al.
Published: (2025)
by: Fu, Mingwei, et al.
Published: (2025)
Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing
by: Goldshlager, Gil, et al.
Published: (2025)
by: Goldshlager, Gil, et al.
Published: (2025)
Gradient is All You Need? How Consensus-Based Optimization can be Interpreted as a Stochastic Relaxation of Gradient Descent
by: Riedl, Konstantin, et al.
Published: (2023)
by: Riedl, Konstantin, et al.
Published: (2023)
The Stochastic Steepest Descent Method for Robust Optimization in Banach Spaces
by: Chada, Neil K., et al.
Published: (2023)
by: Chada, Neil K., et al.
Published: (2023)
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
by: Hwang, Youngsik, et al.
Published: (2024)
by: Hwang, Youngsik, et al.
Published: (2024)
An Inexact General Descent Method with Applications in Differential Equation-Constrained Optimization
by: Macedo, Humberto Gimenes, et al.
Published: (2025)
by: Macedo, Humberto Gimenes, et al.
Published: (2025)
Accelerated Gradient Descent by Concatenation of Stepsize Schedules
by: Zhang, Zehao, et al.
Published: (2024)
by: Zhang, Zehao, et al.
Published: (2024)
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent
by: Bian, Fengmiao, et al.
Published: (2025)
by: Bian, Fengmiao, et al.
Published: (2025)
Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
by: Zhu, Wenqi, et al.
Published: (2024)
by: Zhu, Wenqi, et al.
Published: (2024)
On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality
by: Xia, Lu, et al.
Published: (2023)
by: Xia, Lu, et al.
Published: (2023)
Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels
by: Hertrich, Johannes, et al.
Published: (2022)
by: Hertrich, Johannes, et al.
Published: (2022)
Convergence Analysis of Fractional Gradient Descent
by: Aggarwal, Ashwani
Published: (2023)
by: Aggarwal, Ashwani
Published: (2023)
Block Majorization Minimization with Extrapolation and Application to $β$-NMF
by: Hien, Le Thi Khanh, et al.
Published: (2024)
by: Hien, Le Thi Khanh, et al.
Published: (2024)
Gradient-adjusted underdamped Langevin dynamics for sampling
by: Zuo, Xinzhe, et al.
Published: (2024)
by: Zuo, Xinzhe, et al.
Published: (2024)
Accelerating operator Sinkhorn iteration with overrelaxation
by: Soma, Tasuku, et al.
Published: (2024)
by: Soma, Tasuku, et al.
Published: (2024)
Performance Enhancement of the Recursive Least Squares Algorithms with Rank Two Updates
by: Stotsky, Alexander
Published: (2025)
by: Stotsky, Alexander
Published: (2025)
A Lyapunov Analysis of Accelerated PDHG Algorithms
by: Zeng, Xueying, et al.
Published: (2024)
by: Zeng, Xueying, et al.
Published: (2024)
Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor
by: Miao, Daniel, et al.
Published: (2024)
by: Miao, Daniel, et al.
Published: (2024)
Tight Convergence Rates in Gradient Mapping for the Difference-of-Convex Algorithm
by: Rotaru, Teodor, et al.
Published: (2025)
by: Rotaru, Teodor, et al.
Published: (2025)
A DC-Reformulation for Gradient-$L^0$-Constrained Problems
by: Dittrich, Bastian, et al.
Published: (2025)
by: Dittrich, Bastian, et al.
Published: (2025)
Optimal control of a kinetic equation
by: Pim, Aaron, et al.
Published: (2024)
by: Pim, Aaron, et al.
Published: (2024)
Scalable Approximate Optimal Diagonal Preconditioning
by: Gao, Wenzhi, et al.
Published: (2023)
by: Gao, Wenzhi, et al.
Published: (2023)
Similar Items
-
Projected Block Coordinate Descent for sparse spike estimation
by: Bénard, Pierre-Jean, et al.
Published: (2024) -
Scaled Relative Graph of Normal Matrices
by: Huang, Xinmeng, et al.
Published: (2019) -
Dual Block Gradient Ascent for Entropically Regularised Quantum Optimal Transport
by: Randig, Marvin, et al.
Published: (2025) -
Modified Loss of Momentum Gradient Descent: Fine-Grained Analysis
by: Cattaneo, Matias D., et al.
Published: (2025) -
A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
by: Yuan, Ganzhao
Published: (2023)