Saved in:
| Main Authors: | Bai, Luwei, Hu, Yaohua, Wang, Hao, Yang, Xiaoqi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.09274 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization
by: Bodard, Alexander, et al.
Published: (2025)
by: Bodard, Alexander, et al.
Published: (2025)
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
by: Dirren, Colin, et al.
Published: (2024)
by: Dirren, Colin, et al.
Published: (2024)
An accelerated first-order regularized momentum descent ascent algorithm for stochastic nonconvex-concave minimax problems
by: Zhang, Huiling, et al.
Published: (2023)
by: Zhang, Huiling, et al.
Published: (2023)
Dynamic Proximal Gradient Algorithms for Schatten-$p$ Quasi-Norm Regularized Problems
by: Shen, Weiping, et al.
Published: (2026)
by: Shen, Weiping, et al.
Published: (2026)
Anderson Acceleration in Nonsmooth Problems: Local Convergence via Active Manifold Identification
by: Li, Kexin, et al.
Published: (2024)
by: Li, Kexin, et al.
Published: (2024)
Dealing with unbounded gradients in stochastic saddle-point optimization
by: Neu, Gergely, et al.
Published: (2024)
by: Neu, Gergely, et al.
Published: (2024)
$\ell_{1\text{-}2}$ Regularization for Sparse Optimization: Consistency and Global Convergence
by: Hu, Yaohua, et al.
Published: (2026)
by: Hu, Yaohua, et al.
Published: (2026)
On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem
by: Ding, Kuangyu, et al.
Published: (2025)
by: Ding, Kuangyu, et al.
Published: (2025)
General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization
by: Ahn, Kwangjun, et al.
Published: (2024)
by: Ahn, Kwangjun, et al.
Published: (2024)
Avoidance of non-strict saddle points by blow-up
by: Achour, El Mehdi, et al.
Published: (2025)
by: Achour, El Mehdi, et al.
Published: (2025)
A Globalized Semismooth Newton Method for Prox-regular Optimization Problems
by: Wu, Yuqia, et al.
Published: (2025)
by: Wu, Yuqia, et al.
Published: (2025)
A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization
by: Liu, Wei, et al.
Published: (2025)
by: Liu, Wei, et al.
Published: (2025)
The inexact power augmented Lagrangian method for constrained nonconvex optimization
by: Bodard, Alexander, et al.
Published: (2024)
by: Bodard, Alexander, et al.
Published: (2024)
Adam with model exponential moving average is effective for nonconvex optimization
by: Ahn, Kwangjun, et al.
Published: (2024)
by: Ahn, Kwangjun, et al.
Published: (2024)
Quantization Avoids Saddle Points in Distributed Optimization
by: Bo, Yanan, et al.
Published: (2024)
by: Bo, Yanan, et al.
Published: (2024)
Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian
by: He, Chuan, et al.
Published: (2023)
by: He, Chuan, et al.
Published: (2023)
Block majorization-minimization with diminishing radius for constrained nonsmooth nonconvex optimization
by: Lyu, Hanbaek, et al.
Published: (2020)
by: Lyu, Hanbaek, et al.
Published: (2020)
A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
by: Li, Shuyao, et al.
Published: (2023)
by: Li, Shuyao, et al.
Published: (2023)
Convergence of SGD with momentum in the nonconvex case: A time window-based analysis
by: Qiu, Junwen, et al.
Published: (2024)
by: Qiu, Junwen, et al.
Published: (2024)
Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes
by: Lan, Guanghui, et al.
Published: (2024)
by: Lan, Guanghui, et al.
Published: (2024)
Sinkhorn algorithms and linear programming solvers for optimal partial transport problems
by: Bai, Yikun
Published: (2024)
by: Bai, Yikun
Published: (2024)
Inertial Newton Algorithms Avoiding Strict Saddle Points
by: Castera, Camille
Published: (2021)
by: Castera, Camille
Published: (2021)
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization
by: Akyildiz, Ömer Deniz, et al.
Published: (2020)
by: Akyildiz, Ömer Deniz, et al.
Published: (2020)
Riemannian trust-region methods for strict saddle functions with complexity guarantees
by: Goyens, Florentin, et al.
Published: (2024)
by: Goyens, Florentin, et al.
Published: (2024)
Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning
by: So, Oswin, et al.
Published: (2026)
by: So, Oswin, et al.
Published: (2026)
Randomized coordinate gradient descent almost surely escapes strict saddle points
by: Chen, Ziang, et al.
Published: (2025)
by: Chen, Ziang, et al.
Published: (2025)
Solving Minimum-Cost Reach Avoid using Reinforcement Learning
by: So, Oswin, et al.
Published: (2024)
by: So, Oswin, et al.
Published: (2024)
Long-time dynamics and universality of nonconvex gradient descent
by: Han, Qiyang
Published: (2025)
by: Han, Qiyang
Published: (2025)
Gradient-free algorithm for saddle point problems under overparametrization
by: Statkevich, Ekaterina, et al.
Published: (2024)
by: Statkevich, Ekaterina, et al.
Published: (2024)
An inexact primal-dual method with correction step for a saddle point problem in image debluring
by: Fang, Changjie, et al.
Published: (2021)
by: Fang, Changjie, et al.
Published: (2021)
Stochastic Inverse Problem: stability, regularization and Wasserstein gradient flow
by: Li, Qin, et al.
Published: (2024)
by: Li, Qin, et al.
Published: (2024)
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
by: Zhang, Lijun, et al.
Published: (2023)
by: Zhang, Lijun, et al.
Published: (2023)
Stochastic Trust-Region Methods for Over-parameterized Models
by: Yang, Aike, et al.
Published: (2026)
by: Yang, Aike, et al.
Published: (2026)
Generalization of Silver Stepsize Schedule to Stochastic Optimization
by: Bai, Luwei, et al.
Published: (2025)
by: Bai, Luwei, et al.
Published: (2025)
A convexity preserving nonconvex regularization for inverse problems under non-Gaussian noise
by: Yata, Wataru, et al.
Published: (2025)
by: Yata, Wataru, et al.
Published: (2025)
Efficient Low-rank Identification via Accelerated Iteratively Reweighted Nuclear Norm Minimization
by: Wang, Hao, et al.
Published: (2024)
by: Wang, Hao, et al.
Published: (2024)
Towards An Efficient Approach for the Nonconvex $\ell_p$ Ball Projection: Algorithm and Analysis
by: Yang, Xiangyu, et al.
Published: (2021)
by: Yang, Xiangyu, et al.
Published: (2021)
Sum-of-norms regularized Nonnegative Matrix Factorization
by: Ang, Andersen, et al.
Published: (2024)
by: Ang, Andersen, et al.
Published: (2024)
Infinite-Horizon Reach-Avoid Zero-Sum Games via Deep Reinforcement Learning
by: Li, Jingqi, et al.
Published: (2022)
by: Li, Jingqi, et al.
Published: (2022)
An Iteratively Reweighted Method for Sparse Optimization on Nonconvex $\ell_{p}$ Ball
by: Wang, Hao, et al.
Published: (2021)
by: Wang, Hao, et al.
Published: (2021)
Similar Items
-
Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization
by: Bodard, Alexander, et al.
Published: (2025) -
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
by: Dirren, Colin, et al.
Published: (2024) -
An accelerated first-order regularized momentum descent ascent algorithm for stochastic nonconvex-concave minimax problems
by: Zhang, Huiling, et al.
Published: (2023) -
Dynamic Proximal Gradient Algorithms for Schatten-$p$ Quasi-Norm Regularized Problems
by: Shen, Weiping, et al.
Published: (2026) -
Anderson Acceleration in Nonsmooth Problems: Local Convergence via Active Manifold Identification
by: Li, Kexin, et al.
Published: (2024)