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Vertical Federated Learning

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yankang18/attack-defense-vfl

공식 코드

A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning

https://github.com/yuanxun2024/vflgan

공식 코드

VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication

https://github.com/duanyiyao/E-TS-in-VFL

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit

https://github.com/fedlearnAI/fedlearnalgo

Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform

https://github.com/fedlearnJDT/fedlearn-algo

Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform

https://github.com/isdkfj/binary-attack

Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated Learning

https://github.com/kubeflow/fate-operator

Federated Machine Learning: Concept and Applications

https://github.com/vvv214/OLH

Differentially Private Vertical Federated Clustering

https://github.com/vvv214/ldp_protocols

Differentially Private Vertical Federated Clustering

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.