Saved in:
| Main Authors: | Zhang, Wanyu, Gou, Ruili, Liu, Huikang, Wang, Zhiguo, Ye, Yinyu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.14021 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming
by: Huang, Yicheng, et al.
Published: (2024)
by: Huang, Yicheng, et al.
Published: (2024)
When Does Primal Interior Point Method Beat Primal-dual in Linear Optimization?
by: Gao, Wenzhi, et al.
Published: (2024)
by: Gao, Wenzhi, et al.
Published: (2024)
Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
by: Chen, Yanguang, et al.
Published: (2023)
by: Chen, Yanguang, et al.
Published: (2023)
PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation
by: Liu, Huikang, et al.
Published: (2025)
by: Liu, Huikang, et al.
Published: (2025)
PDHCG-II: An Enhanced Version of PDHCG for Large-Scale Convex QP
by: Li, Hongpei, et al.
Published: (2026)
by: Li, Hongpei, et al.
Published: (2026)
Averaging Orientations with Molecular Symmetry in Cryo-EM
by: Zhang, Qi, et al.
Published: (2023)
by: Zhang, Qi, et al.
Published: (2023)
D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems
by: Li, Hongpei, et al.
Published: (2026)
by: Li, Hongpei, et al.
Published: (2026)
OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
by: Li, Hongpei, et al.
Published: (2025)
by: Li, Hongpei, et al.
Published: (2025)
Convergence of Decentralized Stochastic Subgradient-based Methods for Nonsmooth Nonconvex functions
by: Zhang, Siyuan, et al.
Published: (2024)
by: Zhang, Siyuan, et al.
Published: (2024)
Stochastic Bregman Subgradient Methods for Nonsmooth Nonconvex Optimization Problems
by: Ding, Kuangyu, et al.
Published: (2024)
by: Ding, Kuangyu, et al.
Published: (2024)
On the convergence of doubly stochastic Primal-Dual Hybrid Gradient Method
by: Xiao, Yiheng, et al.
Published: (2026)
by: Xiao, Yiheng, et al.
Published: (2026)
Stochastic Approximation Proximal Subgradient Method for Stochastic Convex-Concave Minimax Optimization
by: Dai, Yu-Hong, et al.
Published: (2024)
by: Dai, Yu-Hong, et al.
Published: (2024)
A Stochastic Conjugate Subgradient Algorithm for Two-stage Stochastic Programming
by: Zhang, Di, et al.
Published: (2025)
by: Zhang, Di, et al.
Published: (2025)
Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness
by: Xie, Chenghan, et al.
Published: (2023)
by: Xie, Chenghan, et al.
Published: (2023)
A Low-Rank ADMM Splitting Approach for Semidefinite Programming
by: Han, Qiushi, et al.
Published: (2024)
by: Han, Qiushi, et al.
Published: (2024)
Subgradient Gliding Method for Nonsmooth Convex Optimization
by: Zhu, Zhihan, et al.
Published: (2026)
by: Zhu, Zhihan, et al.
Published: (2026)
An Efficient Stochastic Subgradient Method for the Global Placement Problem in Very Large-Scale Integration Circuits
by: Yue, Yi-Shuang, et al.
Published: (2024)
by: Yue, Yi-Shuang, et al.
Published: (2024)
Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency
by: Jiang, Yuntian, et al.
Published: (2025)
by: Jiang, Yuntian, et al.
Published: (2025)
A Hybrid Subgradient Method for Nonsmooth Nonconvex Bilevel Optimization
by: Xiao, Nachuan, et al.
Published: (2025)
by: Xiao, Nachuan, et al.
Published: (2025)
The Stochastic Conjugate Subgradient Algorithm For Kernel Support Vector Machines
by: Zhang, Di, et al.
Published: (2024)
by: Zhang, Di, et al.
Published: (2024)
Day-Ahead Offering for Virtual Power Plants: A Stochastic Linear Programming Reformulation and Projected Subgradient Method
by: Meng, Weiqi, et al.
Published: (2026)
by: Meng, Weiqi, et al.
Published: (2026)
Subgradient Methods for Nonsmooth Convex Functions with Adversarial Errors
by: Gösgens, Martijn, et al.
Published: (2025)
by: Gösgens, Martijn, et al.
Published: (2025)
Stochastic Subgradient Methods with Guaranteed Global Stability in Nonsmooth Nonconvex Optimization
by: Xiao, Nachuan, et al.
Published: (2023)
by: Xiao, Nachuan, et al.
Published: (2023)
Policy Optimization in Robust Control: Weak Convexity and Subgradient Methods
by: Watanabe, Yuto, et al.
Published: (2025)
by: Watanabe, Yuto, et al.
Published: (2025)
A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
by: Lin, Zhenwei, et al.
Published: (2024)
by: Lin, Zhenwei, et al.
Published: (2024)
Federated Incremental Subgradient Method for Convex Bilevel Optimization Problems
by: Boontawee, Sudkobfa, et al.
Published: (2026)
by: Boontawee, Sudkobfa, et al.
Published: (2026)
A Tuning-Free Primal-Dual Splitting Algorithm for Large-Scale Semidefinite Programming
by: Wang, Yinjun, et al.
Published: (2024)
by: Wang, Yinjun, et al.
Published: (2024)
Subgradient Splitting Methods for Nonsmooth Fractional Programming with Fixed-Point Constraints
by: Prangprakhon, Mootta, et al.
Published: (2025)
by: Prangprakhon, Mootta, et al.
Published: (2025)
Fixed-Point Delayed Subgradient Methods for Nonsmooth Convex Optimization Problems
by: Pankoon, Ontima, et al.
Published: (2026)
by: Pankoon, Ontima, et al.
Published: (2026)
Stochastic Augmented Lagrangian Method in Riemannian Shape Manifolds
by: Geiersbach, Caroline, et al.
Published: (2023)
by: Geiersbach, Caroline, et al.
Published: (2023)
Stochastic Online Fisher Markets: Static Pricing Limits and Adaptive Enhancements
by: Jalota, Devansh, et al.
Published: (2022)
by: Jalota, Devansh, et al.
Published: (2022)
Adaptive Single-Loop Methods for Stochastic Minimax Optimization on Riemannian Manifolds
by: Wang, Hongye, et al.
Published: (2026)
by: Wang, Hongye, et al.
Published: (2026)
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
by: Tan, Jiyuan, et al.
Published: (2023)
by: Tan, Jiyuan, et al.
Published: (2023)
Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses
by: Jiang, Yuntian, et al.
Published: (2023)
by: Jiang, Yuntian, et al.
Published: (2023)
Riemannian Stochastic Gradient Method for Nested Composition Optimization
by: Zhang, Dewei, et al.
Published: (2022)
by: Zhang, Dewei, et al.
Published: (2022)
Achieving Instance-dependent Sample Complexity for Constrained Markov Decision Process
by: Jiang, Jiashuo, et al.
Published: (2024)
by: Jiang, Jiashuo, et al.
Published: (2024)
Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods
by: He, Chang, et al.
Published: (2023)
by: He, Chang, et al.
Published: (2023)
Gradient Methods with Online Scaling
by: Gao, Wenzhi, et al.
Published: (2024)
by: Gao, Wenzhi, et al.
Published: (2024)
An MILP-Based Solution Scheme for Factored and Robust Factored Markov Decision Processes
by: Liu, Huikang, et al.
Published: (2024)
by: Liu, Huikang, et al.
Published: (2024)
Subgradient sampling for nonsmooth nonconvex minimization
by: Bolte, Jérôme, et al.
Published: (2022)
by: Bolte, Jérôme, et al.
Published: (2022)
Similar Items
-
Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming
by: Huang, Yicheng, et al.
Published: (2024) -
When Does Primal Interior Point Method Beat Primal-dual in Linear Optimization?
by: Gao, Wenzhi, et al.
Published: (2024) -
Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
by: Chen, Yanguang, et al.
Published: (2023) -
PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation
by: Liu, Huikang, et al.
Published: (2025) -
PDHCG-II: An Enhanced Version of PDHCG for Large-Scale Convex QP
by: Li, Hongpei, et al.
Published: (2026)