Cover Image

Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Chang, Jiang, Yuntian, Zhang, Chuwen, Ge, Dongdong, Jiang, Bo, Ye, Yinyu
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Homogeneous Second-Order Descent Method for Nonconvex Optimization
by: Zhang, Chuwen, et al.
Published: (2022)

Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses
by: Jiang, Yuntian, et al.
Published: (2023)

The Second-Order Tâtonnement: Decentralized Interior-Point Methods for Market Equilibrium
by: Zhang, Chuwen, et al.
Published: (2025)

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency
by: Jiang, Yuntian, et al.
Published: (2025)

History-Aware Adaptive High-Order Tensor Regularization
by: He, Chang, et al.
Published: (2025)

A Homogenization Approach for Gradient-Dominated Stochastic Optimization
by: Tan, Jiyuan, et al.
Published: (2023)

An Enhanced ADMM-based Interior Point Method for Linear and Conic Optimization
by: Deng, Qi, et al.
Published: (2022)

Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness
by: Xie, Chenghan, et al.
Published: (2023)

Inexact and Implementable Accelerated Newton Proximal Extragradient Method for Convex Optimization
by: Huang, Ziyu, et al.
Published: (2024)

PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation
by: Liu, Huikang, et al.
Published: (2025)

Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
by: Gao, Wenzhi, et al.
Published: (2024)

Solving Linear Programs with Fast Online Learning Algorithms
by: Gao, Wenzhi, et al.
Published: (2021)

A Practical GPU-Enhanced Matrix-Free Primal-Dual Method for Large-Scale Conic Programs
by: Lin, Zhenwei, et al.
Published: (2025)

cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language
by: Lu, Haihao, et al.
Published: (2023)

A Technical Note on the Implementation and Use of PDCS
by: Lin, Zhenwei, et al.
Published: (2026)

Learning to Pivot as a Smart Expert
by: Liu, Tianhao, et al.
Published: (2023)

A Homogeneous Second-Order Descent Ascent Algorithm for Nonconvex-Strongly Concave Minimax Problems
by: Chen, Jia-Hao, et al.
Published: (2026)

Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming
by: Huang, Yicheng, et al.
Published: (2024)

PDHCG-II: An Enhanced Version of PDHCG for Large-Scale Convex QP
by: Li, Hongpei, et al.
Published: (2026)

A Riemannian Alternating Descent Ascent Algorithmic Framework for Nonconvex-Linear Minimax Problems on Riemannian Manifolds
by: Xu, Meng, et al.
Published: (2024)

From an Interior Point to a Corner Point: Smart Crossover
by: Ge, Dongdong, et al.
Published: (2021)

Achieving Instance-dependent Sample Complexity for Constrained Markov Decision Process
by: Jiang, Jiashuo, et al.
Published: (2024)

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate
by: Jiang, Ruichen, et al.
Published: (2024)

Quadratic Gradient: A Unified Framework Bridging Gradient Descent and Newton-Type Methods by Synthesizing Hessians and Gradients
by: Chiang, John
Published: (2022)

Beyond $\mathcal{O}(\sqrt{T})$ Regret: Decoupling Learning and Decision-making in Online Linear Programming
by: Gao, Wenzhi, et al.
Published: (2025)

Cardinal Optimizer (COPT) User Guide
by: Ge, Dongdong, et al.
Published: (2022)

Vectorized Sparse Second-Order Forward Automatic Differentiation for Optimal Control Direct Methods
by: Zou, Yilin, et al.
Published: (2025)

Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
by: Chen, Yanguang, et al.
Published: (2023)

Adaptive Single-Loop Methods for Stochastic Minimax Optimization on Riemannian Manifolds
by: Wang, Hongye, et al.
Published: (2026)

Local Second-Order Limit Dynamics of the Alternating Direction Method of Multipliers for Semidefinite Programming
by: Kang, Shucheng, et al.
Published: (2026)

Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU
by: Han, Qiushi, et al.
Published: (2024)

First and Second Order Approximations to Stochastic Gradient Descent Methods with Momentum Terms
by: Lu, Eric
Published: (2025)

Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
by: Chu, Ya-Chi, et al.
Published: (2025)

Preconditioned Norms: A Unified Framework for Steepest Descent, Quasi-Newton and Adaptive Methods
by: Veprikov, Andrey, et al.
Published: (2025)

A Riemannian Proximal Newton Method
by: Si, Wutao, et al.
Published: (2023)

A Low-Rank ADMM Splitting Approach for Semidefinite Programming
by: Han, Qiushi, et al.
Published: (2024)

D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems
by: Li, Hongpei, et al.
Published: (2026)

Exploring an Alternative Line-Search Method for Lagrange-Newton Optimization
by: Möller, Ralf
Published: (2026)

A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
by: Lin, Zhenwei, et al.
Published: (2024)

Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
by: Agafonov, Artem, et al.
Published: (2024)