Cover Image

Asynchronous and Stochastic Distributed Resource Allocation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Qiang, Yemini, Michal, Wai, Hoi-To
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Clipping Bias and Remedies
by: Li, Qiang, et al.
Published: (2024)

Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
by: Wang, Xiaolu, et al.
Published: (2024)

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

Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
by: Li, Qiang, et al.
Published: (2024)

Tighter Analysis for Decentralized Stochastic Gradient Method: Impact of Data Homogeneity
by: Li, Qiang, et al.
Published: (2024)

A Stochastic Approximation Approach for Efficient Decentralized Optimization on Random Networks
by: Yau, Chung-Yiu, et al.
Published: (2024)

Byzantine-Resilient Decentralized Online Resource Allocation
by: Wang, Runhua, et al.
Published: (2025)

Asynchronous Distributed Optimization with Delay-free Parameters
by: Wu, Xuyang, et al.
Published: (2023)

Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching
by: Attia, Amit, et al.
Published: (2024)

Optimal Asynchronous Stochastic Nonconvex Optimization under Heavy-Tailed Noise
by: Wu, Yidong, et al.
Published: (2026)

Online Resource Allocation with Non-Stationary Customers
by: Zhang, Xiaoyue, et al.
Published: (2024)

EMA-Nesterov: Stabilizing Nesterov's Lookahead for Accelerated Deep Learning Optimization
by: Yau, Chung-Yiu, et al.
Published: (2026)

Asynchronous Message-Passing and Zeroth-Order Optimization Based Distributed Learning with a Use-Case in Resource Allocation in Communication Networks
by: Behmandpoor, Pourya, et al.
Published: (2023)

Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches
by: Dereziński, Michał
Published: (2022)

Robust Out-of-Distribution Stochastic Optimization
by: Li, Xianyu, et al.
Published: (2026)

A Finite-Iteration Theory for Asynchronous Categorical Distributional Temporal-Difference Learning
by: Kaya, Ege C., et al.
Published: (2026)

Stochastic Newton Proximal Extragradient Method
by: Jiang, Ruichen, et al.
Published: (2024)

Federated Majorize-Minimization: Beyond Parameter Aggregation
by: Dieuleveut, Aymeric, et al.
Published: (2025)

Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model
by: An, Lin, et al.
Published: (2024)

Online Optimization for Randomized Network Resource Allocation with Long-Term Constraints
by: Sid-Ali, Ahmed, et al.
Published: (2023)

Exponentially Weighted Algorithm for Online Network Resource Allocation with Long-Term Constraints
by: Sid-Ali, Ahmed, et al.
Published: (2024)

Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
by: Tyurin, Alexander, et al.
Published: (2024)

Communication-Efficient Stochastic Distributed Learning
by: Ren, Xiaoxing, et al.
Published: (2025)

Optimization Trade-offs in Asynchronous Federated Learning: A Stochastic Networks Approach
by: Alahyane, Abdelkrim, et al.
Published: (2026)

Online Resource Allocation with Average Budget Constraints
by: Ao, Ruicheng, et al.
Published: (2024)

An Asynchronous Decentralised Optimisation Algorithm for Nonconvex Problems
by: Mafakheri, Behnam, et al.
Published: (2025)

Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics
by: He, Zhiyu, et al.
Published: (2025)

Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization
by: Guo, Luyao, et al.
Published: (2023)

Central Limit Theorems for Asynchronous Averaged Q-Learning
by: Liu, Xingtu
Published: (2025)

Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data
by: Liu, Haitong, et al.
Published: (2023)

Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
by: Gao, Wenzhi, et al.
Published: (2024)

Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
by: Domingo-Enrich, Carles, et al.
Published: (2024)

Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity
by: Shi, Qiankun, et al.
Published: (2025)

Nested Stochastic Algorithm for Generalized Sinkhorn distance-Regularized Distributionally Robust Optimization
by: Yang, Yufeng, et al.
Published: (2025)

ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
by: Maranjyan, Artavazd, et al.
Published: (2025)

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
by: Maity, Sreejeet, et al.
Published: (2025)

Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates
by: Paul, Anik Kumar, et al.
Published: (2026)

Revisiting Multi-Agent Asynchronous Online Optimization with Delays: the Strongly Convex Case
by: Bao, Lingchan, et al.
Published: (2025)

Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
by: Jing, Gangshan, et al.
Published: (2021)

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
by: Gorbunov, Eduard, et al.
Published: (2023)