Cover Image

Stochastic Gradient Descent for Constrained Optimization based on Adaptive Relaxed Barrier Functions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dimitrieski, Naum, Cao, Jing, Ebenbauer, Christian
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Time-delay Induced Stochastic Optimization and Extremum Seeking
by: Dimitrieski, Naum, et al.
Published: (2024)

Global Stability and Step Size Robustness of RMSProp
by: Dimitrieski, Naum, et al.
Published: (2026)

A Poisson Jump-driven SDE Approach to Distributed Gradient Descent with Sparse Communication
by: Weber, Marc, et al.
Published: (2025)

Stochastic Gradient Descent with Adaptive Data
by: Che, Ethan, et al.
Published: (2024)

Flexible-step Model Predictive Control based on Generalized Lyapunov Functions
by: Fürnsinn, Annika, et al.
Published: (2022)

Decentralized Relaxed Smooth Optimization with Gradient Descent Methods
by: Jiang, Zhanhong, et al.
Published: (2025)

Stochastic Adaptive Gradient Descent Without Descent
by: Aujol, Jean-François, et al.
Published: (2025)

Projected Gradient Descent for Constrained Decision-Dependent Optimization
by: Wang, Zifan, et al.
Published: (2025)

A Communication-Efficient Stochastic Gradient Descent Algorithm for Distributed Nonconvex Optimization
by: Xie, Antai, et al.
Published: (2024)

Flexible-step MPC for Switched Linear Systems with No Quadratic Common Lyapunov Function
by: Fürnsinn, Annika, et al.
Published: (2024)

Generalized Stochastic Gradient Descent with Momentum Methods for Smooth Optimization
by: Wang, Zimeng, et al.
Published: (2026)

Adaptive Accelerated Gradient Descent Methods for Convex Optimization
by: Xu, Zeyi, et al.
Published: (2026)

An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method
by: Zhang, Jiahao, et al.
Published: (2024)

Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent
by: Köhne, Frederik, et al.
Published: (2023)

On a Family of Relaxed Gradient Descent Methods for Quadratic Minimization
by: MacDonald, Liam, et al.
Published: (2024)

Functional Central Limit Theorem for Stochastic Gradient Descent
by: Flamand, Kessang, et al.
Published: (2026)

The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)

Gradient is All You Need? How Consensus-Based Optimization can be Interpreted as a Stochastic Relaxation of Gradient Descent
by: Riedl, Konstantin, et al.
Published: (2023)

Using Stochastic Gradient Descent to Smooth Nonconvex Functions: Analysis of Implicit Graduated Optimization
by: Sato, Naoki, et al.
Published: (2023)

Descent-Net: Learning Descent Directions for Constrained Optimization
by: Zhou, Zisheng, et al.
Published: (2025)

Robust and structure exploiting optimization algorithms: An integral quadratic constraint approach
by: Michalowsky, Simon, et al.
Published: (2019)

Inferring Global Exponential Stability Properties using Lie-bracket Approximations
by: Weber, Marc, et al.
Published: (2024)

Non-Local Extremum Seeking Based on the Divergence Theorem
by: Suttner, Raik, et al.
Published: (2026)

Global Extremum Seeking With Double Integrators in the Presence of Local Extrema
by: Suttner, Raik, et al.
Published: (2026)

Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
by: Vansover-Hager, Shira, et al.
Published: (2025)

A Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimax Optimization
by: Zhu, Yuchen, et al.
Published: (2024)

Control Barrier Function Based Design of Gradient Flows for Constrained Nonlinear Programming
by: Allibhoy, Ahmed, et al.
Published: (2022)

Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness
by: Crawshaw, Michael, et al.
Published: (2025)

Stochastic Modified Equations for Stochastic Gradient Descent in Infinite-Dimensional Hilbert Spaces
by: Cerrai, Sandra, et al.
Published: (2026)

Stochastic Gradient Descent with Strategic Querying
by: Jiang, Nanfei, et al.
Published: (2025)

GeoAdaLer: Geometric Insights into Adaptive Stochastic Gradient Descent Algorithms
by: Eleh, Chinedu, et al.
Published: (2024)

Adaptive Conditional Gradient Descent
by: Khademi, Abbas, et al.
Published: (2025)

Gradient Descent, Stochastic Optimization, and Other Tales
by: Lu, Jun
Published: (2022)

Distributed Adaptive Gradient Algorithm with Gradient Tracking for Stochastic Non-Convex Optimization
by: Han, Dongyu, et al.
Published: (2024)

StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
by: Mazouz, Rayan, et al.
Published: (2026)

Adaptive Gradient Descent on Riemannian Manifolds with Nonnegative Curvature
by: Ansari-Önnestam, Aban, et al.
Published: (2025)

Gradient Descent for Convex and Smooth Noisy Optimization
by: Hu, Feifei, et al.
Published: (2024)

Composing Optimized Stepsize Schedules for Gradient Descent
by: Grimmer, Benjamin, et al.
Published: (2024)

Improving the Robustness of the Projected Gradient Descent Method for Nonlinear Constrained Optimization Problems in Topology Optimization
by: Barbeau, Lucka, et al.
Published: (2024)

Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent
by: Sato, Naoki, et al.
Published: (2024)