Cover Image

A single-loop SPIDER-type stochastic subgradient method for expectation-constrained nonconvex nonsmooth optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Wei, Xu, Yangyang
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control Computational Complexity Machine Learning Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise
by: Fang, Yuchen, et al.
Published: (2025)

On Approximate Computation of Critical Points
by: Ahmadi, Amir Ali, et al.
Published: (2026)

A direct optimization algorithm for input-constrained MPC
by: Wu, Liang, et al.
Published: (2023)

Backtracking New Q-Newton's method, Newton's flow, Voronoi's diagram and Stochastic root finding
by: Fornaess, John Erik, et al.
Published: (2024)

First-order methods for stochastic and finite-sum convex optimization with deterministic constraints
by: Lu, Zhaosong, et al.
Published: (2025)

On the numerical reliability of nonsmooth autodiff: a MaxPool case study
by: Boustany, Ryan
Published: (2024)

Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
by: Dereich, Steffen, et al.
Published: (2024)

Block majorization-minimization with diminishing radius for constrained nonsmooth nonconvex optimization
by: Lyu, Hanbaek, et al.
Published: (2020)

A distributed semismooth Newton based augmented Lagrangian method for distributed optimization
by: Ma, Qihao, et al.
Published: (2026)

Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems
by: Dereich, Steffen, et al.
Published: (2025)

Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance
by: Stollenwerk, Alexander, et al.
Published: (2024)

PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning
by: Jentzen, Arnulf, et al.
Published: (2025)

Regularized methods via cubic model subspace minimization for nonconvex optimization
by: Bellavia, Stefania, et al.
Published: (2023)

Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees
by: Lu, Zhaosong, et al.
Published: (2024)

Continuum-marginal optimal transport: a mesh-free kernel method
by: Nakano, Yumiharu
Published: (2026)

Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient
by: Lim, Dong-Young, et al.
Published: (2022)

Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes
by: Lan, Guanghui, et al.
Published: (2024)

Optimal Preconditioning is a Geodesically Convex Optimization Problem
by: Doğan, M. Levent, et al.
Published: (2025)

An unfitted finite element method for PDE-constrained shape optimization via shape gradient flow
by: Gong, Wei, et al.
Published: (2026)

IETI-based Low-Rank method for PDE-constrained optimization
by: Bünger, Alexandra, et al.
Published: (2024)

Computing AD-compatible subgradients of convex relaxations of implicit functions
by: Song, Yingkai, 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)

Differentiable Singular Value Decomposition
by: Kanchi, Rohit, et al.
Published: (2025)

Online Covariance Matrix Estimation in Sketched Newton Methods
by: Kuang, Wei, et al.
Published: (2025)

Cubic regularized subspace Newton for non-convex optimization
by: Zhao, Jim, et al.
Published: (2024)

RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees
by: Laufer, Eilon Vaknin, et al.
Published: (2025)

Horoballs and the subgradient method
by: Lewis, Adrian S., et al.
Published: (2024)

Neural incomplete factorization: learning preconditioners for the conjugate gradient method
by: Häusner, Paul, et al.
Published: (2023)

sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
by: Xu, Renjie, et al.
Published: (2025)

The inexact power augmented Lagrangian method for constrained nonconvex optimization
by: Bodard, Alexander, et al.
Published: (2024)

Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
by: Liang, Luxu, et al.
Published: (2024)

Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models
by: Tomasetto, Matteo, et al.
Published: (2024)

A novel dual-decomposition method for non-convex two-stage stochastic mixed-integer quadratically constrained quadratic problems
by: Belyak, Nikita, et al.
Published: (2023)

A first-order method for nonconvex-strongly-concave constrained minimax optimization
by: Lu, Zhaosong, et al.
Published: (2025)

PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python
by: Goujaud, Baptiste, et al.
Published: (2022)

Convergence of Adam for Non-convex Objectives: Relaxed Hyperparameters and Non-ergodic Case
by: He, Meixuan, et al.
Published: (2023)

Benign landscape for Burer-Monteiro factorizations of MaxCut-type semidefinite programs
by: Endor, Faniriana Rakoto, et al.
Published: (2024)

UAdam: Unified Adam-Type Algorithmic Framework for Non-Convex Stochastic Optimization
by: Jiang, Yiming, et al.
Published: (2023)

A multigrid solver for PDE-constrained optimization with uncertain inputs
by: Ciaramella, Gabriele, et al.
Published: (2023)

From PDEs constrained optimization to controllability problems via time domain decomposition
by: Cocquet, Pierre-Henri, et al.
Published: (2026)