DLFi – The Distributed Learning Framework

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      Conventional ML training has the safety concern of collecting all data in a single place and violating the privacy of the data owners. DLFi aims to solve this. 

      DLFi is a Privacy-Preserving AI-as-as-Service (PP-AIaaS) solution. It provides a training environment on remote sites without necessarily displacing or transferring the data. It enables data providers to train a ML model without revealing their business-critical data to each other. DLFi offers communication-efficiency and guarantees the privacy of data owners.

      Features

      • Privacy-Preserving
      • Cloud-Native
      • Modular and Pluggable
      • Customized Visualization Dashboard
      • GPU-Acceleration Support

      Applications

      • ML Model Training over Geo-distributed Data Sources
      • Collaborative ML Model Training in Multi-domain Multi-vendor and Disaggregated Networks
      • Shared Governance and Ownership of ML Models

      Implemented Use-cases

      • QoT Estimation in Multi-domain Multi-vendor Optical Networks
      • Vision Inspection for Quality Assurance in Factory Shop Floors

      Relevant Projects

      Previous Demonstrations

      • Demonstration of Federated Learning over Edge-Computing Enabled Metro Optical Networks at ECOC 2020

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