Image de couverture de livre

A Saddle Point Remedy: Power of Variable Elimination in Non-convex Optimization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Gan, Min, Chen, Guang-Yong, Yi, Yang, Yang, Lin
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Regret Minimization via Saddle Point Optimization
par: Kirschner, Johannes, et autres
Publié: (2024)

Federated Composite Saddle Point Optimization
par: Bai, Site, et autres
Publié: (2023)

Quantization Avoids Saddle Points in Distributed Optimization
par: Bo, Yanan, et autres
Publié: (2024)

Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints
par: Yang, Ming, et autres
Publié: (2025)

Efficiently Escaping Saddle Points for Policy Optimization
par: Khorasani, Sadegh, et autres
Publié: (2023)

Simultaneous Learning and Optimization via Misspecified Saddle Point Problems
par: Ahmadi, Mohammad Mahdi, et autres
Publié: (2025)

Dimension-Free Saddle-Point Escape in Muon
par: Long, Yanlin, et autres
Publié: (2026)

Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape
par: Liu, Yuankai, et autres
Publié: (2024)

Proximal Point Method for Online Saddle Point Problem
par: Meng, Qing-xin, et autres
Publié: (2024)

Online Min-Max Optimization: From Individual Regrets to Cumulative Saddle Points
par: Vyas, Abhijeet, et autres
Publié: (2026)

Bilevel Optimization over Saddle Points of Zero-Sum Markov Games
par: Zheng, Zihao, et autres
Publié: (2026)

Progressive Power Homotopy for Non-convex Optimization
par: Xu, Chen
Publié: (2026)

Online Non-convex Optimization with Long-term Non-convex Constraints
par: Pan, Shijie, et autres
Publié: (2023)

Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
par: Zhang, Qi, et autres
Publié: (2024)

Inertial Newton Algorithms Avoiding Strict Saddle Points
par: Castera, Camille
Publié: (2021)

Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training
par: Hu, Yue, et autres
Publié: (2025)

Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
par: Cutkosky, Ashok, et autres
Publié: (2023)

Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance
par: Chen, Hongxu, et autres
Publié: (2026)

Differentially Private Non-convex Distributionally Robust Optimization
par: Xu, Difei, et autres
Publié: (2026)

Stochastic Momentum Methods for Non-smooth Non-Convex Finite-Sum Coupled Compositional Optimization
par: Chen, Xingyu, et autres
Publié: (2025)

Saddle-to-Saddle Dynamics Explains A Simplicity Bias Across Neural Network Architectures
par: Zhang, Yedi, et autres
Publié: (2025)

Stochastic Gradient Descent in the Saddle-to-Saddle Regime of Deep Linear Networks
par: Corlouer, Guillaume, et autres
Publié: (2026)

Efficiently Escaping Saddle Points under Generalized Smoothness via Self-Bounding Regularity
par: Cao, Daniel Yiming, et autres
Publié: (2025)

Retraction-Free Decentralized Non-convex Optimization with Orthogonal Constraints
par: Sun, Youbang, et autres
Publié: (2024)

On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms
par: Kovalev, Dmitry, et autres
Publié: (2024)

Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
par: Yamamoto, Naoya, et autres
Publié: (2025)

Random Scaling and Momentum for Non-smooth Non-convex Optimization
par: Zhang, Qinzi, et autres
Publié: (2024)

Saddle-To-Saddle Dynamics in Deep ReLU Networks: Low-Rank Bias in the First Saddle Escape
par: Bantzis, Ioannis, et autres
Publié: (2025)

Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance
par: Zhang, Qi, et autres
Publié: (2024)

WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
par: Li, Dongyue, et autres
Publié: (2026)

Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation
par: Beznosikov, Aleksandr, et autres
Publié: (2026)

Non-convex Stochastic Composite Optimization with Polyak Momentum
par: Gao, Yuan, et autres
Publié: (2024)

Review Non-convex Optimization Method for Machine Learning
par: Fotopoulos, Greg B, et autres
Publié: (2024)

A Stochastic Quasi-Newton Method for Non-convex Optimization with Non-uniform Smoothness
par: Sun, Zhenyu, et autres
Publié: (2024)

From Saddle Points Toward Global Minima: A Newton-Type Method on Wasserstein Space
par: Lascu, Razvan-Andrei, et autres
Publié: (2026)

A Latent Variable Approach for Non-Hierarchical Multi-Fidelity Adaptive Sampling
par: Chen, Yi-Ping, et autres
Publié: (2023)

Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach
par: Li, Yinan, et autres
Publié: (2023)

Enhancing Stability of Physics-Informed Neural Network Training Through Saddle-Point Reformulation
par: Bylinkin, Dmitry, et autres
Publié: (2025)

Escaping Saddle Points for Nonsmooth Weakly Convex Functions via Perturbed Proximal Algorithms
par: Huang, Minhui, et autres
Publié: (2021)

DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization
par: Li, Anjian, et autres
Publié: (2024)