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Search results for jupyter notebook federated learning
federated-learning
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jupyter-notebook
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33 search results found
Fedlab
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612
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.
Easyfl
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395
An experimental platform to quickly realize and compare with popular centralized federated learning algorithms. A realization of federated learning algorithm on fairness (FedFV, Federated Learning with Fair Averaging, https://fanxlxmu.github.io/publication/ijcai2021/) was accepted by IJCAI-21 (https://www.ijcai.org/proceedings/2021/223).
Federa
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107
FedERA is a modular and fully customizable open-source FL framework, aiming to address these issues by offering comprehensive support for heterogeneous edge devices and incorporating both standalone and distributed computing. It includes new software modules to enhance usability and promote environ- mental sustainability.
Distributed Learning Contributivity
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48
Simulate collaborative ML scenarios, experiment multi-partner learning approaches and measure respective contributions of different datasets to model performance.
Self Balancing Federated Learning
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43
Implementation of the paper "Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems"
Dl_notebooks
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42
This repo contains all the notebooks mentioned in blog.
Decentralized Ml
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42
Full stack service enabling decentralized machine learning on private data
Soteria
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38
Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
Federated Ml
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26
Detect anomalies in network traffic data using Federated Machine Learning technique.
Fed_iot_guard
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21
Detection of IoT devices infected by malwares from their network communications, using federated machine learning
Fl Ml
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20
This is official code for ACIIDS2022 paper "Meta-learning and Personalization layer in Federated learning"
Recsys2021 Pursuing Privacy
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18
Material supporting the tutorial "Pursuing Privacy in Recommender Systems: The View of Users and Researchers from Regulations to Applications" held at the 15th ACM Conference on Recommender Systems in Amsterdam, Netherlands
Fedpa
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18
Federated posterior averaging implemented in JAX
Federated Learning And Split Learning With Raspberry Pi
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17
SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
Playground
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16
Playground code. Things that have been deprecated but may be useful in the future.
Ai Ml
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15
A curated list of machine learning and AI projects.
Done
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14
Federated Learning using PyTorch. Second-Order for Federated Learning. (IEEE Transactions on Parallel and Distributed Systems 2022)
Privacy Preserving Bandits
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14
Privacy-Preserving Bandits (MLSys'20)
Srijan Gsoc 2020
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12
Healthcare-Researcher-Connector Package: Federated Learning tool for bridging the gap between Healthcare providers and researchers
Pets Bootcamp
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11
A collection of demos and utilities prepared ahead of the Vector Institute Privacy Enhancing Techniques (PETs) Bootcamp.
Dw Fedavg
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10
A Federated Learning based Android Malware Classification System
Paddle Fl Gui
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9
基于PaddleFL框架的联邦学习医疗影像识别GUI
Bde
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9
Blossom development environment, pre-build
Visionair
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7
Runner's Up submission under The Marconi Society's Celestini Prize India. This repository entails my contributions to our project VisionAir : A privacy-preserving smartphone application that can be used to estimate the Air Quality Index from an image that the user takes. The application uses On-Device training to ensure complete isolation of the user's private data and also uses federated learning to diversify the response of the global deep learning model iteratively
Ad_fl_dl
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7
Apply Federated Learning and Deep Learning (Deep Auto-encoder) to detect abnormal data for IoT devices.
Decentralized Ml
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7
Interoperable and decentralized machine learning.
Data Free Ensemble Selection For One Shot Federated Learning
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6
Data-Free Ensemble Selection For One-Shot Federated Learning
Grokking Deep Learning Notebooks
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5
Notes & Code to go over "Grokking Deep Learning" Book by Andrew Trask
Al Based Fl For Multi Task Disaster Detection Model
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5
We design a multi-task model for joint disaster classification and victim detection. We train the model using both the Centralized Learning (CL) and Federated Learning (FL) methods. We also tried Active Learning (AL) to see how it could help in reducing the labeling workload for disaster dataset. Lastly, we optimized the model using OpenVINO.
4d Fedgnn Plus
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5
Federating temporally-varying graph timeseries
Federated Knowledge Alignment
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5
Federated Learning
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5
An implementation of Federated Learning using Pytorch and PySyft
Korean_voice_phishing_detection
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5
All codes implemented on Korean voice phishing detection papers
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