PulseAugur
EN
LIVE 17:28:25
ENTITY Decentralized federated learning system

Decentralized federated learning system

PulseAugur coverage of Decentralized federated learning system — every cluster mentioning Decentralized federated learning system across labs, papers, and developer communities, ranked by signal.

Show in brief
Total · 30d
6
6 over 90d
Releases · 30d
0
0 over 90d
Papers · 30d
6
6 over 90d
TIER MIX · 90D
TOPICS
RELATIONSHIPS
SENTIMENT · 30D

4 day(s) with sentiment data

RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_129270 ·

    New framework optimizes topology selection for decentralized federated learning

    Researchers have introduced AIRPLAN, a novel framework for optimizing topology selection in Over-the-Air Decentralized Federated Learning (OTA-DFL). By drawing an analogy between OTA-DFL and distributed query processing…

  2. TOOL · CL_115724 ·

    New architecture enables decentralized orchestration for fluid AI and IoT

    A new paper proposes a decentralized orchestration architecture for fluid computing environments, aiming to improve resource management across heterogeneous devices like end devices, edge infrastructure, and cloud platf…

  3. TOOL · CL_111704 ·

    New WFAgg algorithm enhances security in Decentralized Federated Learning

    Researchers have developed a new Byzantine-robust aggregation algorithm called WFAgg for Decentralized Federated Learning (DFL). This algorithm is designed to enhance security in DFL environments by identifying and miti…

  4. TOOL · CL_93818 ·

    SPARK method accelerates decentralized federated learning with stable NTK updates

    Researchers have developed SPARK, a novel method to improve the convergence speed and stability of decentralized federated learning (DFL) under heterogeneous data conditions. SPARK utilizes a stage-wise annealed soft-la…

  5. TOOL · CL_70225 ·

    New decentralized EM algorithms improve Gaussian mixture modeling in federated learning

    Researchers have developed new decentralized algorithms for Gaussian mixture models in federated learning settings. These methods, including a momentum-based approach (MNEM) and a semi-supervised variant (semi-MNEM), ad…

  6. RESEARCH · CL_36595 ·

    New research advances federated learning with proactive client selection and privacy analysis

    Researchers are exploring new methods to improve federated learning, a technique for training models across decentralized data sources while preserving privacy. One approach, "Choose Wisely and Privately," uses mutual i…