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Federated Learning

Federated learning is originally created by Google. With the help of Federated Learning, machine learning models can learn on data sets located in different sites without having any training information shared between them.

Google Introduces ‘PipelineDP’: A New Differential Privacy Framework For Python Developers...

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Google unveiled a new milestone. a differential privacy framework, along with OpenMined that lets any Python developer handle data with differential privacy.  The two have been working on...

Introduction To Federated Learning: Enabling The Scaling Of Machine Learning Across...

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Large volumes of data are required for training machine learning models. The trained model is run on a cloud server that users can access...

JAX + Flower For Federated Learning Gives Machine Learning Researchers The...

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Google researchers created JAX to conduct NumPy computations on GPUs and TPUs. DeepMind uses it to help and expedite its research, and it is...

Hierarchical Federated Learning-Based Anomaly Detection Using Digital Twins For Internet of...

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Smart healthcare services can be provided by using Internet of Things (IoT) technologies that monitor the health conditions of patients and their vital body...

Google’s Latest Machine Learning Research on Using Differential Privacy in Image...

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From recommendations to automatic picture classification, machine learning (ML) models are increasingly helpful for increased performance across several consumer products. Despite aggregating massive volumes...

Google AI Implements Machine Learning Model That Employs Federated Learning With...

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Bringing model training to the device extends beyond the usage of local models that make predictions on mobile devices. Federated Learning (FL) allows mobile...

Being Compatible With Any Programming Language And Machine Learning Framework; Flower...

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Flower is an end-to-end federated learning framework that allows for a smoother transition from simulation-based experimental research to system research on many real-world edge...

Researchers from MIT CSAIL Introduce ‘Privid’: an AI Tool, Build on...

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This research summary article is based on the paper 'Privid: Practical, Privacy-Preserving Video Analytics Queries' and MIT article 'Security tool guarantees privacy in surveillance...

Google AI Introduces ‘Federated Reconstruction’ Framework That Enables Scalable Partially Local...

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Federated learning is a machine learning technique in which an algorithm is trained across numerous decentralized edge devices or servers, keeping local data samples...

Ericsson And Uppsala University Team Up To Research Air Quality Prediction...

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Statistical methods have recently been applied in various sectors, spanning from health care to customer relationship management, to analyze and forecast the behavior of...
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