Copertina

SADDLe: Sharpness-Aware Decentralized Deep Learning with Heterogeneous Data

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Choudhary, Sakshi, Aketi, Sai Aparna, Roy, Kaushik
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Distributed, Parallel, and Cluster Computing Multiagent Systems
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Averaging Rate Scheduler for Decentralized Learning on Heterogeneous Data
di: Aketi, Sai Aparna, et al.
Pubblicazione: (2024)

Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
di: Ravikumar, Deepak, et al.
Pubblicazione: (2023)

Communication-Efficient Personalized Distributed Learning with Data and Node Heterogeneity
di: Tian, Zhuojun, et al.
Pubblicazione: (2025)

On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning
di: Zhu, Tongtian, et al.
Pubblicazione: (2025)

Optimizing Decentralized Online Learning for Supervised Regression and Classification Problems
di: Kruijssen, J. M. Diederik, et al.
Pubblicazione: (2025)

Multi-Agent Bandit Learning through Heterogeneous Action Erasure Channels
di: Hanna, Osama A., et al.
Pubblicazione: (2023)

Decentralized Task Offloading and Load-Balancing for Mobile Edge Computing in Dense Networks
di: Yahya, Mariam, et al.
Pubblicazione: (2024)

BIPPO: Budget-Aware Independent PPO for Energy-Efficient Federated Learning Services
di: Lackinger, Anna, et al.
Pubblicazione: (2025)

SureFED: Robust Federated Learning via Uncertainty-Aware Inward and Outward Inspection
di: Heydaribeni, Nasimeh, et al.
Pubblicazione: (2023)

Single-Loop Federated Actor-Critic across Heterogeneous Environments
di: Zhu, Ye, et al.
Pubblicazione: (2024)

OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning
di: Ye, Rui, et al.
Pubblicazione: (2024)

DICE: Data Influence Cascade in Decentralized Learning
di: Zhu, Tongtian, et al.
Pubblicazione: (2025)

Merit-Based Sortition in Decentralized Systems
di: Kruijssen, J. M. Diederik, et al.
Pubblicazione: (2024)

Multitask Learning with Learned Task Relationships
di: Wan, Zirui, et al.
Pubblicazione: (2025)

A Unified Framework for Center-based Clustering of Distributed Data
di: Armacki, Aleksandar, et al.
Pubblicazione: (2024)

When Computing follows Vehicles: Decentralized Mobility-Aware Resource Allocation for Edge-to-Cloud Continuum
di: Nezami, Zeinab, et al.
Pubblicazione: (2024)

Asynchronous Local Computations in Distributed Bayesian Learning
di: Bhar, Kinjal, et al.
Pubblicazione: (2023)

Compressed Federated Reinforcement Learning with a Generative Model
di: Beikmohammadi, Ali, et al.
Pubblicazione: (2024)

AGMARL-DKS: An Adaptive Graph-Enhanced Multi-Agent Reinforcement Learning for Dynamic Kubernetes Scheduling
di: Hamzeh, Hamed
Pubblicazione: (2026)

Collaborative Learning of On-Device Small Model and Cloud-Based Large Model: Advances and Future Directions
di: Niu, Chaoyue, et al.
Pubblicazione: (2025)

MARS: Efficient, Adaptive Co-Scheduling for Heterogeneous Agentic Systems
di: Wang, Yifei, et al.
Pubblicazione: (2026)

CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
di: Huang, Kun, et al.
Pubblicazione: (2023)

Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planning
di: Li, Qingbiao, et al.
Pubblicazione: (2020)

Quantized Decentralized Stochastic Learning over Directed Graphs
di: Taheri, Hossein, et al.
Pubblicazione: (2020)

Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence
di: Jordan, Philip, et al.
Pubblicazione: (2024)

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models
di: Gu, Yile, et al.
Pubblicazione: (2025)

On Collaboration in Distributed Parameter Estimation with Resource Constraints
di: Chen, Yu-Zhen Janice, et al.
Pubblicazione: (2023)

Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning
di: Mohammadabadi, Seyed Mahmoud Sajjadi, et al.
Pubblicazione: (2024)

Intelligent Offloading in Vehicular Edge Computing: A Comprehensive Review of Deep Reinforcement Learning Approaches and Architectures
di: Uddin, Ashab, et al.
Pubblicazione: (2025)

ISFL: Federated Learning for Non-i.i.d. Data with Local Importance Sampling
di: Zhu, Zheqi, et al.
Pubblicazione: (2022)

Ensuring Fair LLM Serving Amid Diverse Applications
di: Khan, Redwan Ibne Seraj, et al.
Pubblicazione: (2024)

Collaborative Multi-Agent Heterogeneous Multi-Armed Bandits
di: Chawla, Ronshee, et al.
Pubblicazione: (2023)

Holonic Learning: A Flexible Agent-based Distributed Machine Learning Framework
di: Esmaeili, Ahmad, et al.
Pubblicazione: (2023)

Distributed Fractional Bayesian Learning for Adaptive Optimization
di: Yang, Yaqun, et al.
Pubblicazione: (2024)

Sustainability of Data Center Digital Twins with Reinforcement Learning
di: Sarkar, Soumyendu, et al.
Pubblicazione: (2024)

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
di: Liu, Shuo, et al.
Pubblicazione: (2026)

Fully Distributed Fog Load Balancing with Multi-Agent Reinforcement Learning
di: Ebrahim, Maad, et al.
Pubblicazione: (2024)

Incentivizing Multi-Tenant Split Federated Learning for Foundation Models at the Network Edge
di: Li, Songyuan, et al.
Pubblicazione: (2025)

Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
di: Mhanna, Elissa, et al.
Pubblicazione: (2024)

Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks
di: Song, Zhuoqing, et al.
Pubblicazione: (2021)