~/talk

FedLess: Secure and Scalable Serverless Federated Learning

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FedLess is an open‑source, cloud‑agnostic serverless FL framework that runs client functions on AWS Lambda, Google Cloud Functions and Azure Functions, uses MongoDB as parameter server, is written in Python 3 with TensorFlow/Keras support, and applies local differential privacy (Gaussian noise) by default. It implements a semi‑asynchronous FedScan strategy using DBSCAN clustering and staleness‑aware aggregation, demonstrates up to 200 concurrent clients, speeds convergence enough to cut training time ~8% and cost ~20%, and raises final accuracy ~2% with 70 simulated stragglers.

AI-written summary · about

  1. 0:00FedLess introduction
  2. 1:03Cloud computing evolution
  3. 4:52Federated Learning basics
  4. 7:03Serverless + Federated Learning
  5. 8:11FedLess architecture
  6. 13:25Addressing stragglers in Federated Learning
  7. 20:55Results and cost analysis
  8. 24:50Personalized models
  9. 28:03Q&A
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