Copertina

Faster Stochastic ADMM for Nonsmooth Composite Convex Optimization in Hilbert Space

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Deng, Weihua, Song, Haiming, Wang, Hao, Yang, Jinda
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Optimization and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Single-loop Stochastic Riemannian ADMM for Nonsmooth Optimization
di: Jin, Jiachen, et al.
Pubblicazione: (2025)

A Unified Inexact Stochastic ADMM for Composite Nonconvex and Nonsmooth Optimization
di: Zeng, Yuxuan, et al.
Pubblicazione: (2024)

ADMM for Nonsmooth Composite Optimization under Orthogonality Constraints
di: Yuan, Ganzhao
Pubblicazione: (2024)

Adaptive Riemannian ADMM for Nonsmooth Optimization: Optimal Complexity without Smoothing
di: Deng, Kangkang, et al.
Pubblicazione: (2025)

Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
di: Chen, Lesi, et al.
Pubblicazione: (2023)

An Inexact Alternating Direction Method of Multipliers for Constrained Parabolic Optimal Distributed Control Problems
di: Song, Haiming, et al.
Pubblicazione: (2026)

Heterogeneous Stochastic Momentum ADMM for Distributed Nonconvex Composite Optimization
di: Zhang, Yangming, et al.
Pubblicazione: (2026)

Subgame Perfect Methods in Nonsmooth Convex Optimization
di: Grimmer, Benjamin, et al.
Pubblicazione: (2025)

Subgradient Gliding Method for Nonsmooth Convex Optimization
di: Zhu, Zhihan, et al.
Pubblicazione: (2026)

Inexact Zeroth-Order Nonsmooth and Nonconvex Stochastic Composite Optimization and Applications
di: Pougkakiotis, Spyridon, et al.
Pubblicazione: (2025)

The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach
di: Song, Yongcun, et al.
Pubblicazione: (2023)

Zeroth-Order Methods for Stochastic Nonconvex Nonsmooth Composite Optimization
di: Chen, Ziyi, et al.
Pubblicazione: (2025)

An Inexact Proximal Framework for Nonsmooth Riemannian Difference-of-Convex Optimization
di: Jiang, Bo, et al.
Pubblicazione: (2025)

The Stochastic Multi-Proximal Method for Nonsmooth Optimization
di: Condat, Laurent, et al.
Pubblicazione: (2025)

Distributed Prediction-Correction ADMM for Time-Varying Convex Optimization
di: Bastianello, Nicola, et al.
Pubblicazione: (2020)

Stochastic ADMM with batch size adaptation for nonconvex nonsmooth optimization
di: Jin, Jiachen, et al.
Pubblicazione: (2025)

An Efficient ADMM Method for Ratio-Type Nonconvex and Nonsmooth Minimization in Sparse Recovery
di: Yu, Lang, et al.
Pubblicazione: (2025)

Fixed-Point Delayed Subgradient Methods for Nonsmooth Convex Optimization Problems
di: Pankoon, Ontima, et al.
Pubblicazione: (2026)

HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization
di: Tran, Trinh, et al.
Pubblicazione: (2026)

A Nesterov-Accelerated Primal-Dual Splitting Algorithm for Convex Nonsmooth Optimization
di: Condat, Laurent, et al.
Pubblicazione: (2026)

High-Resolution Inertial Dynamics with Time-Rescaled Gradients for Nonsmooth Convex Optimization
di: Le, Manh Hung, et al.
Pubblicazione: (2026)

Locally Linear Convergence for Nonsmooth Convex Optimization via Coupled Smoothing and Momentum
di: Baghbadorani, Reza Rahimi, et al.
Pubblicazione: (2025)

A New Inexact Gradient Descent Method with Applications to Nonsmooth Convex Optimization
di: Khanh, Pham Duy, et al.
Pubblicazione: (2023)

Stochastic Bregman Subgradient Methods for Nonsmooth Nonconvex Optimization Problems
di: Ding, Kuangyu, et al.
Pubblicazione: (2024)

Perturbed Proximal Gradient ADMM for Nonconvex Composite Optimization
di: Zhou, Yuan, et al.
Pubblicazione: (2025)

A Proximal Variable Smoothing for Nonsmooth Minimization Involving Weakly Convex Composite with MIMO Application
di: Kume, Keita, et al.
Pubblicazione: (2024)

Faster Algorithms for User-Level Private Stochastic Convex Optimization
di: Lowy, Andrew, et al.
Pubblicazione: (2024)

Subgradient Methods for Nonsmooth Convex Functions with Adversarial Errors
di: Gösgens, Martijn, et al.
Pubblicazione: (2025)

Faster Newton Methods for Convex and Nonconvex Optimization in Gradient Complexity
di: Chen, Lesi, et al.
Pubblicazione: (2025)

A Partition-Based Implementation of the Relaxed ADMM for Distributed Convex Optimization over Lossy Networks
di: Bastianello, Nicola, et al.
Pubblicazione: (2018)

Dynamic Systems Coupled with Solutions of Stochastic Nonsmooth Convex Optimization
di: Luo, Jianfeng, et al.
Pubblicazione: (2025)

Stochastic ISTA/FISTA Adaptive Step Search Algorithms for Convex Composite Optimization
di: Nguyen, Lam M., et al.
Pubblicazione: (2024)

New Characterizations of Nonsmooth Convex Functions via Generalized Derivatives
di: Phat, Vo Thanh
Pubblicazione: (2026)

New Outer Approximation Algorithms for Nonsmooth Convex MINLP Problems
di: Wei, Zhou, et al.
Pubblicazione: (2026)

Zeroth-order Gradient and Quasi-Newton Methods for Nonsmooth Nonconvex Stochastic Optimization
di: Marrinan, Luke, et al.
Pubblicazione: (2023)

Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity
di: Gao, Wenzhi, et al.
Pubblicazione: (2024)

Stochastic Bounded Real Lemma and $H_{\infty}$ Control of Difference Systems in Hilbert Spaces
di: Li, Cheng'ao, et al.
Pubblicazione: (2026)

A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
di: Wang, Bokun, et al.
Pubblicazione: (2023)

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization
di: Liu, Zijian, et al.
Pubblicazione: (2025)

Computational Methods and Verification Theorem for Portfolio-Consumption Optimization under Exponential O-U Dynamics
di: Zhong, Zhaoxiang, et al.
Pubblicazione: (2025)