Vertical Federated Learning Paper Lists

Conferences

• Faster Secure Data Mining via Distributed Homomorphic Encryption [paper] [KDD 2020]
• Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data [paper] [KDD 2020]
• Privacy Preserving Vertical Federated Learning for Tree-based Models [paper] [VLDB 2020]
• Measure Contribution of Participants in Federated Learning [paper] [Big Data 2019]
• FDML: A collaborative machine learning framework for distributed features [paperKDD 2019]

Workshops

• A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression [Paper] [NIPS 2019 Workshop]
• A Communication-Efficient Collaborative Learning Framework for Distributed Features [paper] [NIPS 2019 workshop]
• Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator [paper] [IJCAI 2019 workshop]

arxiv

• Optimization for Large-Scale Machine Learning with Distributed Features and Observations [paper] [arxiv 16.10]
• Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption [paper] [arxiv 17.11]
• Entity Resolution and Federated Learning get a Federated Resolution [paper] [arxiv 18.03]
• Split learning for health: Distributed deep learning without sharing raw patient data [paper] [arxiv 18.12]
• Stochastic Distributed Optimization for Machine Learning from Decentralized Features [paper] [arxiv 18.12]
• SecureBoost: A Lossless Federated Learning Framework [paper] [arxiv 19.01]
• Learning Privately over Distributed Features: An ADMM Sharing Approach [paper] [arxiv 19.07]
• Multi-Participant Multi-Class Vertical Federated Learning [paper] [arxiv 20.01]
• Asymmetrical Vertical Federated Learning [paper] [arxiv 20.04]
• VAFL: a Method of Vertical Asynchronous Federated Learning [paper] [arxiv 20.07]
• FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training [paper] [arxiv 20.08]
• Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning [paper] [arxiv 20.08]
• Hybrid Differentially Private Federated Learning on Vertically Partitioned Data [paper] [arxiv 20.09]
• A vertical federated learning method for interpretable scorecard and its application in credit scoring [arxiv 20.09]
• Feature Inference Attack on Model Predictions in Vertical Federated Learning [paper] [arxiv 20.10]
• FederBoost: Private Federated Learning for GBDT [paper] [arxiv 20.11]
• Privacy Leakage of Real-World Vertical Federated Learning [paper] [arxiv 20.11]
• Large-Scale Kernel Method for Vertical Federated Learning [paper] [Federated Learning - Privacy and Incentive ] [20.11]
• Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning [paper] [arxiv 20.11]
• A homomorphic-encryption-based vertical federated learning scheme for rick management [arxiv 2020]
• Accelerating intra-party communication in vertical federated learning [CoNEXT 2020]

Papers on vertically partioned data

• [2003] - Privacy-preserving k-means clustering over vertically partitioned data [paper] [KDD 2003]
• [2002] - Privacy preserving association rule mining in vertically partitioned data [paper] [KDD 2002]
• [2006] - Privacy-Preserving SVM Classification on Vertically Partitioned Data [paper] [PAKDD 2006]
• [2008] - Privacy-preserving decision trees over vertically partitioned data [paper] [TKDD 2008]
• [2008] - A Survey of Privacy-Preserving Methods Across Vertically Partitioned Data [paper]
• Secure linear regression on vertically partitioned datasets [paper] [IACR Cryptol 2016]
• A new privacy-preserving proximal support vector machine for classification of vertically partitioned data [paper] [International Journal of Machine Learning and Cybernetics 2015]
• Privacy preserving random decision tree classification over horizontally and vertically partitioned data [paper] [DASC/PiCom/DataCom/CyberSciTech 2018]