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Project Florence Literature Review · cho.sh

Project Florence Literature Review

Project Florence Literature Review

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Qiang Yang et al. Federated Machine Learning Concept and Applications
Tian Li et al. Federated Learning Challenges, Methods, and Future Directions
Daniele Romanini et al. PyVertical
Record Linkage
FederatedAI/FATE: An Industrial Grade Federated Learning Framework: Did they implement VFL. Yes. FATE/doc/2.0/fate/ml/hetero_secureboost_tutorial.ipynb at v2.0.0-beta · FederatedAI/FATE
Nicola Rieke et al. The future of digital health with federated learning
Qinbin Li et al. Federated Learning Systems. Vision, Hype, and Reality for Data Privacy and Protection

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Project Florence

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Peter Kairouz et al. Advances and Open Problems in Federated Learning

Jose Luis Ambite et al. Secure & Private Federated Neuroimaging

Yuncheng Wu et al. Privacy-Preserving Vertical Federated Learning for Tree-based Models

Xinjian Luo et al. Feature Inference Attack on Model Predictions in Vertical Federated Learning

Yang Liu et al. Asymmetrical Vertical Federated Learning

Tianyi Chen et al. VAFL a Method of Vertical Asynchronous Federated Learning

Siwei Feng et al. Multi-Participant Multi-Class Vertical Federated Learning

Yang Liu et al. Vertical Federated Learning

Kang Wei et al. Vertical Federated Learning, Challenges, Methodologies and Experiments

Shengwen Yang et al. Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator

Qiang Yang et al. Chapter 5 Vertical Federated Learning

PSI

A federated learning algorithm using a parallel-ensemble method on non-IID datasets | Complex & Intelligent Systems

A Survey on Vertical Federated Learning: From a Layered Perspective

Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning

Multi-Participant Vertical Federated Learning Based Time Series Prediction

Federated Auto-Meta-Ensemble Learning Framework for AI-Enabled Military Operations

Online Bagging and Boosting Definition, Online Bagging and Boosting Use in ML

A survey on federated learning: challenges and applications

Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study

Achieving Differential Privacy in Vertically Partitioned Multiparty Learning

Federated Learning for NLP

Split Training, Vertical Partitioning, SplitNN-driven Vertical Partitioning

Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption

Split Learning Project: MIT Media Lab

SplitNN-driven Vertical Partitioning

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