Cover Image

Progressive Power Homotopy for Non-convex Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Xu, Chen
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control Artificial Intelligence Machine Learning 65K05, 68T07, 90C30, 68W40
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Power Homotopy for Zeroth-Order Non-Convex Optimizations
by: Xu, Chen
Published: (2025)

Global Optimization with A Power-Transformed Objective and Gaussian Smoothing
by: Xu, Chen
Published: (2024)

Convergence of iterates and improved rates for accelerated augmented Lagrangian methods for linearly constrained convex optimization
by: He, Xin, et al.
Published: (2026)

On the boundedness of the sequence generated by minibatch stochastic gradient descent
by: Bauschke, Heinz H., et al.
Published: (2025)

Delayed Feedback in Online Non-Convex Optimization: A Non-Stationary Approach with Applications
by: Lara, Felipe, et al.
Published: (2024)

An Augmented Lagrangian Method for Training Recurrent Neural Networks
by: Wang, Yue, et al.
Published: (2024)

Objective Value Change and Shape-Based Accelerated Optimization for the Neural Network Approximation
by: Xie, Pengcheng, et al.
Published: (2025)

Convergence Conditions for Stochastic Line Search Based Optimization of Over-parametrized Models
by: Lapucci, Matteo, et al.
Published: (2024)

Effectively Leveraging Momentum Terms in Stochastic Line Search Frameworks for Fast Optimization of Finite-Sum Problems
by: Lapucci, Matteo, et al.
Published: (2024)

A Layer Separation Optimization Framework for Cross-Entropy Training in Deep Learning
by: Liu, Yaru, et al.
Published: (2026)

Distributed Gradient-Regularized Newton Method: Scheduled Consensus and O(epsilon^{-1}) Global Iteration Complexity
by: Hu, Wei, et al.
Published: (2026)

Faster Adaptive Optimization via Expected Gradient Outer Product Reparameterization
by: DePavia, Adela, et al.
Published: (2025)

NOVAK: Unified adaptive optimizer for deep neural networks
by: Kavun, Sergii
Published: (2026)

Losing momentum in continuous-time stochastic optimisation
by: Jin, Kexin, et al.
Published: (2022)

Spectrally Constrained Optimization
by: Garner, Casey, et al.
Published: (2023)

General Constrained Matrix Optimization
by: Garner, Casey, et al.
Published: (2024)

Distributed Computing for Huge-Scale Aggregative Convex Programming
by: Tao, Luoyi
Published: (2026)

Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization
by: Xu, Ruoran, et al.
Published: (2026)

Sample-wise Constrained Learning via a Sequential Penalty Approach with Applications in Image Processing
by: Lanzillotta, Francesca, et al.
Published: (2026)

Primal-Dual Coordinate Descent for Nonconvex-Nonconcave Saddle Point Problems Under the Weak MVI Assumption
by: Walwil, Iyad, et al.
Published: (2025)

The Challenges of Optimization For Data Science
by: Varner, Christian, et al.
Published: (2024)

An Analysis of Optimizer Choice on Energy Efficiency and Performance in Neural Network Training
by: Almog, Tom
Published: (2025)

On the fast convergence of minibatch heavy ball momentum
by: Bollapragada, Raghu, et al.
Published: (2022)

Error Bound Analysis for the Regularized Loss of Deep Linear Neural Networks
by: Chen, Po, et al.
Published: (2025)

Preconditioned subgradient method for composite optimization: overparameterization and fast convergence
by: Díaz, Mateo, et al.
Published: (2025)

The Güler-type acceleration for proximal gradient, linearized augmented Lagrangian and linearized alternating direction method of multipliers
by: Zhou, Bin, et al.
Published: (2025)

SVD-Preconditioned Gradient Descent Method for Solving Nonlinear Least Squares Problems
by: Chang, Zhipeng, et al.
Published: (2026)

A Novel Gradient Methodology with Economical Objective Function Evaluations for Data Science Applications
by: Varner, Christian, et al.
Published: (2023)

A Novel First-order Method with Event-driven Objective Evaluations
by: Varner, Christian, et al.
Published: (2025)

Similarity-based fuzzy clustering scientific articles: potentials and challenges from mathematical and computational perspectives
by: Huong, Vu Thi, et al.
Published: (2025)

RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs
by: Niu, Yi-Shuai
Published: (2026)

Recent Advances in Non-convex Smoothness Conditions and Applicability to Deep Linear Neural Networks
by: Patel, Vivak, et al.
Published: (2024)

A distributed proximal splitting method with linesearch for locally Lipschitz gradients
by: Atenas, Felipe, et al.
Published: (2024)

Fast Stochastic Second-Order Adagrad for Nonconvex Bound-Constrained Optimization
by: Bellavia, S., et al.
Published: (2025)

BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization
by: Zhang, Hengrui, et al.
Published: (2026)

The Speed-Robustness Trade-Off for First-Order Methods with Additive Gradient Noise
by: Van Scoy, Bryan, et al.
Published: (2021)

A Heuristic Alternating Direction Method of Multipliers Framework for Distributed and Centralized Tree-Constrained Optimization: Applications to Hop-Constrained Spanning Tree Multicommodity Flow Design
by: Mokhtari, Yacine
Published: (2025)

A Representation Optimization Dichotomy, Lie-Algebraic Policy Optimization
by: KC, Sooraj, et al.
Published: (2026)

Stable gradient-adjusted root mean square propagation on least squares problem
by: Li, Runze, et al.
Published: (2024)

Riemannian Federated Learning via Averaging Gradient Streams
by: Huang, Zhenwei, et al.
Published: (2024)