Awesome-Vertical-Federated-Split-Learning

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Awesome-Vertical-Federated-Split-Learning

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A summay of existing works on vertical federated/split learning

Awesome-Vertical-Federated-Split-Learning 최신버젼 다운로드

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# Awesome-Vertical-Federated-Split-Learning

## 2021 Conference or Journal
Title | Publication  | Team/Authors  | Methods
:------: | :------: | :------: | :------:
[Unleashing the tiger: Inference attacks on split learning](https://arxiv.org/abs/2012.02670) |  CCS  |EPFL/George Mason University|
[VF2Boost: Very fast vertical federated gradient boosting for cross-enterprise learning](https://dl.acm.org/doi/abs/10.1145/3448016.3457241) | SIGMOD| Peking University/Tencent|
[Label inference attacks against vertical federated learning](https://nesa.zju.edu.cn/download/fc_pdf_label_infer.pdf) |  USENIX Security  |Zhejiang University|
[CAFE: Catastrophic data leakage in vertical federated learning](https://arxiv.org/abs/2110.15122) | NeurIPS|Rensselaer Polytechnic Institute/IBM Research |
[AsySQN: Faster vertical federated learning algorithms with better computation resource utilization](https://dl.acm.org/doi/abs/10.1145/3447548.3467169) | KDD| Xidian University & JD Tech |
[Feature inference attack on model predictions in vertical federated learning](https://arxiv.org/abs/2010.10152) |  IEEE ICDE  | National University of Singapore |
[Secure bilevel asynchronous vertical federated learning with backward updating](https://ojs.aaai.org/index.php/AAAI/article/view/17301) | AAAI | Xidian University  |  
[Privacy-Preserving Asynchronous Vertical Federated Learning Algorithms for Multiparty Collaborative Learning](https://arxiv.org/abs/1812.03288) | TNNLS | Mohamed bin Zayed University of Artificial Intelligence/Xidian University  | 
[Large-scale Secure XGB for Vertical Federated Learning](https://dl.acm.org/doi/abs/10.1145/3459637.348236) | CIKM | Ant Group | 
[Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm](https://dl.acm.org/doi/pdf/10.1145/3459637.3482249) | CIKM | Xidian University| 
[Defending against Reconstruction Attack in Vertical Federated Learning](https://fl-icml.github.io/2021/papers/FL-ICML21_paper_21.pdf) |  ICML Workshop  | Bytedance |
[Vertical Federated Learning for Higher-Order Factorization Machines](https://link.springer.com/chapter/10.1007/978-3-030-75765-6_28/) |  PAKDD  |Hokkaido University |
[Multi-tier federated learning for vertically partitioned data](https://link.springer.com/chapter/10.1007/978-3-030-75765-6_28/) |  ICASSP  |Rensselaer Polytechnic Institute|
[Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study](https://medinform.jmir.org/2021/6/e26598/) |  JMIR Med. Inform.  | Yonsei University College of Medicine |

## 2021 Arxiv
Title | Team/Authors | Methods
:------: | :------: | :------: 
[Achieving Model Fairness in Vertical Federated Learning](https://arxiv.org/abs/2109.08344) |  University of Victoria/Huawei |
[PIVODL: Privacy-preserving vertical federated learning over distributed labels](https://arxiv.org/abs/2108.11444) | University of Surrey |
[A Vertical Federated Learning Framework for Horizontally Partitioned Labels](https://arxiv.org/abs/2106.10056) |  Peking University | 
[Exploiting Record Similarity for Practical Vertical Federated Learning](https://arxiv.org/pdf/2106.06312.pdf) |  National University of Singapore |
[A Vertical Federated Learning Framework for Graph Convolutional Network](https://arxiv.org/abs/2106.11593) |  Ant Group |

## 2020 Conference or Journal
Title | Publication  | Team/Authors  | Methods
:------: | :------: | :------: | :------:
[Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data](https://dl.acm.org/doi/abs/10.1145/3394486.3403298) | KDD | JD Finance America Corporation|
[Privacy Preserving Vertical Federated Learning for Tree-based Models](http://www.vldb.org/pvldb/vol13/p2090-wu.pdf) | VLDB Journal | National University of Singapore/Zhejiang University|
[Federated learning for vision-and-language grounding problems](https://ojs.aaai.org/index.php/AAAI/article/view/6824) | AAAI | Peking University/Tencent|
[Split Deep Q-Learning for Robust Object Singulation](https://ieeexplore.ieee.org/abstract/document/9196647) | ICRA | Aristotle University of Thessaloniki|
[VAFL: a Method of Vertical Asynchronous Federated Learning](https://arxiv.org/abs/2007.06081) | ICML Workshop | Rensselaer Polytechnic Institute/UCLA  |
[FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training](https://arxiv.org/abs/2008.10838v1) | IJCAI Workshop | WeBank|
[End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things](https://ieeexplore.ieee.org/abstract/document/9252066) | SRDS | Data61, CSIRO|
[Communication-Efficient Multimodal Split Learning for mmWave Received Power Prediction](https://ieeexplore.ieee.org/abstract/document/9026781) | IEEE Communications Letters | Kyoto University|
[Privacy-Sensitive Parallel Split Learning](https://ieeexplore.ieee.org/abstract/document/9016486) | ICOIN | Chung-Ang University|
[Combining split and federated architectures for efficiency and privacy in deep learning](https://dl.acm.org/doi/abs/10.1145/3386367.3431678) | CONEXT | Saint Louis University|

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