Copertina

Stochastic Momentum Methods for Non-smooth Non-Convex Finite-Sum Coupled Compositional Optimization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Xingyu, Wang, Bokun, Yang, Ming, Lin, Qihang, Yang, Tianbao
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints
di: Yang, Ming, et al.
Pubblicazione: (2025)

Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization
di: Hu, Quanqi, et al.
Pubblicazione: (2023)

A Note on Complexity for Two Classes of Structured Non-Smooth Non-Convex Compositional Optimization
di: Yao, Yao, et al.
Pubblicazione: (2024)

Stochastic Primal-Dual Double Block-Coordinate for Two-way Partial AUC Maximization
di: Zhou, Linli, et al.
Pubblicazione: (2025)

A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
di: Wei, Xiyuan, et al.
Pubblicazione: (2026)

Deterministic and Stochastic Accelerated Gradient Method for Convex Semi-Infinite Optimization
di: Yao, Yao, et al.
Pubblicazione: (2023)

Non-convex Stochastic Composite Optimization with Polyak Momentum
di: Gao, Yuan, et al.
Pubblicazione: (2024)

Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems
di: Zhong, Yanjie, et al.
Pubblicazione: (2024)

On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
di: Wang, Bokun, et al.
Pubblicazione: (2024)

Random Scaling and Momentum for Non-smooth Non-convex Optimization
di: Zhang, Qinzi, et al.
Pubblicazione: (2024)

Inexact Moreau Envelope Lagrangian Method for Non-Convex Constrained Optimization under Local Error Bound Conditions on Constraint Functions
di: Huang, Yankun, et al.
Pubblicazione: (2025)

Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
di: Balmaseda, Vicente, et al.
Pubblicazione: (2025)

Stochastic Difference-of-Convex Optimization with Momentum
di: Chayti, El Mahdi, et al.
Pubblicazione: (2025)

Convergence Analysis of the PAGE Stochastic Algorithm for Weakly Convex Finite-Sum Optimization
di: Condat, Laurent, et al.
Pubblicazione: (2025)

Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
di: Pan, Xiaokang, et al.
Pubblicazione: (2024)

Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning
di: Qi, Qi, et al.
Pubblicazione: (2024)

More Optimal Fractional-Order Stochastic Gradient Descent for Non-Convex Optimization Problems
di: Partohaghighi, Mohammad, et al.
Pubblicazione: (2025)

Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
di: Hu, Quanqi, et al.
Pubblicazione: (2024)

Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Data
di: Qiu, Pu, et al.
Pubblicazione: (2026)

Second-Order Convergence in Private Stochastic Non-Convex Optimization
di: Tao, Youming, et al.
Pubblicazione: (2025)

Online Non-Stationary Stochastic Quasar-Convex Optimization
di: Pun, Yuen-Man, et al.
Pubblicazione: (2024)

Stochastic Non-Smooth Convex Optimization with Unbounded Gradients
di: Kovalev, Dmitry
Pubblicazione: (2026)

Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
di: Cutkosky, Ashok, et al.
Pubblicazione: (2023)

Universal Online Convex Optimization Meets Second-order Bounds
di: Zhang, Lijun, et al.
Pubblicazione: (2021)

DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization
di: Li, Gang, et al.
Pubblicazione: (2025)

Convergence of Spectral Descent for Non-smooth Optimization
di: Yang, Yixuan, et al.
Pubblicazione: (2026)

Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
di: Buckingham, Jack M., et al.
Pubblicazione: (2024)

Multi-Output Distributional Fairness via Post-Processing
di: Li, Gang, et al.
Pubblicazione: (2024)

Learning to Rank with Top-$K$ Fairness
di: Zhang, Boyang, et al.
Pubblicazione: (2025)

Optimal Rates for Robust Stochastic Convex Optimization
di: Gao, Changyu, et al.
Pubblicazione: (2024)

Breaking the Limits of Open-Weight CLIP: An Optimization Framework for Self-supervised Fine-tuning of CLIP
di: Mehta, Anant, et al.
Pubblicazione: (2026)

Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization
di: Liu, Wei, et al.
Pubblicazione: (2025)

New Lower Bounds for Stochastic Non-Convex Optimization through Divergence Decomposition
di: Saad, El Mehdi, et al.
Pubblicazione: (2025)

Stochastic Approximation Approaches to Group Distributionally Robust Optimization and Beyond
di: Zhang, Lijun, et al.
Pubblicazione: (2023)

DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation
di: Guo, Siqi, et al.
Pubblicazione: (2026)

Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis
di: Jiao, Yang, et al.
Pubblicazione: (2023)

Stochastic Compositional Optimization via Hybrid Momentum Frank--Wolfe
di: Chayti, El Mahdi
Pubblicazione: (2026)

Negative Momentum for Convex-Concave Optimization
di: Shugart, Henry, et al.
Pubblicazione: (2026)

Non-Convex Optimization with Spectral Radius Regularization
di: Sandler, Adam, et al.
Pubblicazione: (2021)