A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Lei, Liu, Xin |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking
por: Chen, Jun, et al.
Publicado: (2025)
por: Chen, Jun, et al.
Publicado: (2025)
High-Probability Convergence in Decentralized Stochastic Optimization with Gradient Tracking
por: Armacki, Aleksandar, et al.
Publicado: (2026)
por: Armacki, Aleksandar, et al.
Publicado: (2026)
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints
por: Ablin, Pierre, et al.
Publicado: (2023)
por: Ablin, Pierre, et al.
Publicado: (2023)
Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
por: Keane, Ronan
Publicado: (2024)
por: Keane, Ronan
Publicado: (2024)
A Double Tracking Method for Optimization with Decentralized Generalized Orthogonality Constraints
por: Wang, Lei, et al.
Publicado: (2024)
por: Wang, Lei, et al.
Publicado: (2024)
A Support-Set Algorithm for Optimization Problems with Nonnegative and Orthogonal Constraints
por: Wang, Lei, et al.
Publicado: (2025)
por: Wang, Lei, et al.
Publicado: (2025)
Variance-Reduced Cascade Q-learning: Algorithms and Sample Complexity
por: Boveiri, Mohammad, et al.
Publicado: (2024)
por: Boveiri, Mohammad, et al.
Publicado: (2024)
Enhancing Convergence of Decentralized Gradient Tracking under the KL Property
por: Chen, Xiaokai, et al.
Publicado: (2024)
por: Chen, Xiaokai, et al.
Publicado: (2024)
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
por: Chen, Jun, et al.
Publicado: (2023)
por: Chen, Jun, et al.
Publicado: (2023)
Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization
por: Sahinoglu, Emre, et al.
Publicado: (2024)
por: Sahinoglu, Emre, et al.
Publicado: (2024)
On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization
por: Liang, Ling, et al.
Publicado: (2024)
por: Liang, Ling, et al.
Publicado: (2024)
Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance
por: Chen, Hongxu, et al.
Publicado: (2026)
por: Chen, Hongxu, et al.
Publicado: (2026)
Retraction-Free Decentralized Non-convex Optimization with Orthogonal Constraints
por: Sun, Youbang, et al.
Publicado: (2024)
por: Sun, Youbang, et al.
Publicado: (2024)
Hierarchical Decentralized Stochastic Control for Cyber-Physical Systems
por: Kaza, Kesav, et al.
Publicado: (2025)
por: Kaza, Kesav, et al.
Publicado: (2025)
Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization
por: Liu, Wei, et al.
Publicado: (2025)
por: Liu, Wei, et al.
Publicado: (2025)
A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds
por: Wang, Lei, et al.
Publicado: (2024)
por: Wang, Lei, et al.
Publicado: (2024)
Safe Gradient Flow for Bilevel Optimization
por: Sharifi, Sina, et al.
Publicado: (2025)
por: Sharifi, Sina, et al.
Publicado: (2025)
Variance-Reduced Gradient Estimator for Nonconvex Zeroth-Order Distributed Optimization
por: Mu, Huaiyi, et al.
Publicado: (2024)
por: Mu, Huaiyi, et al.
Publicado: (2024)
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning
por: Chakrabarti, Kushal, et al.
Publicado: (2022)
por: Chakrabarti, Kushal, et al.
Publicado: (2022)
NPGA: A Unified Algorithmic Framework for Decentralized Constraint-Coupled Optimization
por: Li, Jingwang, et al.
Publicado: (2022)
por: Li, Jingwang, et al.
Publicado: (2022)
Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics
por: He, Zhiyu, et al.
Publicado: (2025)
por: He, Zhiyu, et al.
Publicado: (2025)
Stochastic Gradient Langevin Dynamics with Variance Reduction
por: Huang, Zhishen, et al.
Publicado: (2021)
por: Huang, Zhishen, et al.
Publicado: (2021)
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
por: Li, Huan, et al.
Publicado: (2021)
por: Li, Huan, et al.
Publicado: (2021)
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems
por: Muehlebach, Michael, et al.
Publicado: (2021)
por: Muehlebach, Michael, et al.
Publicado: (2021)
A Concise Lyapunov Analysis of Nesterov's Accelerated Gradient Method
por: Liu, Jun
Publicado: (2025)
por: Liu, Jun
Publicado: (2025)
Learning to Sparsify Stochastic Linear Bandits
por: Wang, Zhengmiao, et al.
Publicado: (2026)
por: Wang, Zhengmiao, et al.
Publicado: (2026)
Online Convex Optimization and Integral Quadratic Constraints: An automated approach to regret analysis
por: Jakob, Fabian, et al.
Publicado: (2025)
por: Jakob, Fabian, et al.
Publicado: (2025)
Evaluation of Prosumer Networks for Peak Load Management in Iran: A Distributed Contextual Stochastic Optimization Approach
por: Noori, Amir, et al.
Publicado: (2024)
por: Noori, Amir, et al.
Publicado: (2024)
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
por: Chen, Lesi, et al.
Publicado: (2022)
por: Chen, Lesi, et al.
Publicado: (2022)
Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
por: Ye, Lintao, et al.
Publicado: (2022)
por: Ye, Lintao, et al.
Publicado: (2022)
Optimized Gradient Tracking for Decentralized Online Learning
por: Sharma, Shivangi Dubey, et al.
Publicado: (2023)
por: Sharma, Shivangi Dubey, et al.
Publicado: (2023)
Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks
por: Song, Zhuoqing, et al.
Publicado: (2021)
por: Song, Zhuoqing, et al.
Publicado: (2021)
Variance-Reduced $(\varepsilon,δ)-$Unlearning using Forget Set Gradients
por: Van Waerebeke, Martin, et al.
Publicado: (2026)
por: Van Waerebeke, Martin, et al.
Publicado: (2026)
A Distributed Gradient-based Algorithm for Optimization Problems with Coupled Equality Constraints
por: Qiu, Chenyang, et al.
Publicado: (2025)
por: Qiu, Chenyang, et al.
Publicado: (2025)
Towards Weaker Variance Assumptions for Stochastic Optimization
por: Alacaoglu, Ahmet, et al.
Publicado: (2025)
por: Alacaoglu, Ahmet, et al.
Publicado: (2025)
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods
por: Chayti, El Mahdi, et al.
Publicado: (2023)
por: Chayti, El Mahdi, et al.
Publicado: (2023)
Breaking the Stochasticity Barrier: An Adaptive Variance-Reduced Method for Variational Inequalities
por: Jeong, Yungi, et al.
Publicado: (2026)
por: Jeong, Yungi, et al.
Publicado: (2026)
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
por: Chen, Lesi, et al.
Publicado: (2023)
por: Chen, Lesi, et al.
Publicado: (2023)
On the Gradient Domination of the LQG Problem
por: Fallah, Kasra, et al.
Publicado: (2025)
por: Fallah, Kasra, et al.
Publicado: (2025)
Anytime Acceleration of Gradient Descent
por: Zhang, Zihan, et al.
Publicado: (2024)
por: Zhang, Zihan, et al.
Publicado: (2024)
Ejemplares similares
-
Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking
por: Chen, Jun, et al.
Publicado: (2025) -
High-Probability Convergence in Decentralized Stochastic Optimization with Gradient Tracking
por: Armacki, Aleksandar, et al.
Publicado: (2026) -
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints
por: Ablin, Pierre, et al.
Publicado: (2023) -
Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
por: Keane, Ronan
Publicado: (2024) -
A Double Tracking Method for Optimization with Decentralized Generalized Orthogonality Constraints
por: Wang, Lei, et al.
Publicado: (2024)