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2011.02796
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FederBoost: Private Federated Learning for GBDT
5 November 2020
Zhihua Tian
Rui Zhang
Xiaoyang Hou
Jian Liu
K. Ren
Jian Liu
Kui Ren
FedML
AI4CE
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Papers citing
"FederBoost: Private Federated Learning for GBDT"
50 / 53 papers shown
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TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems
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09 Jun 2025
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Bilateral Differentially Private Vertical Federated Boosted Decision Trees
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Haodong Jiang
Wenshu Fan
Lihao Zheng
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Shuaiting Huang
Junfeng Wu
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30 Apr 2025
Tree-based Models for Vertical Federated Learning: A Survey
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Yuexiang Xie
Yaliang Li
Bolin Ding
Jingren Zhou
FedML
308
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03 Apr 2025
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Wei Shen
Bo Du
E. Snezhko
Vassili Kovalev
PongChi Yuen
FedML
376
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25 May 2024
A Federated Learning Benchmark on Tabular Data: Comparing Tree-Based Models and Neural Networks
International Conference on Fog and Mobile Edge Computing (FMEC), 2023
William Lindskog
Christian Prehofer
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247
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Histogram-Based Federated XGBoost using Minimal Variance Sampling for Federated Tabular Data
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Christian Prehofer
Sarandeep Singh
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204
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0
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A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
Lei Yu
Meng Han
Yiming Li
Changting Lin
Yao Zhang
...
Yan Liu
Haiqin Weng
Yuseok Jeon
Ka-Ho Chow
Stacy Patterson
FedML
335
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M. Hayashitani
Junki Mori
Isamu Teranishi
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424
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Starlit: Privacy-Preserving Federated Learning to Enhance Financial Fraud Detection
Aydin Abadi
Bradley Doyle
Francesco Gini
Kieron Guinamard
S. K. Murakonda
...
Steven J. Murdoch
Mohammad Naseri
Hector Page
George Theodorakopoulos
Suzanne Weller
344
20
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19 Jan 2024
Effective and Efficient Federated Tree Learning on Hybrid Data
International Conference on Learning Representations (ICLR), 2023
Qinbin Li
Chulin Xie
Xiaojun Xu
Xiaoyuan Liu
Ce Zhang
Yue Liu
Bingsheng He
Basel Alomair
FedML
268
4
0
18 Oct 2023
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning
Tianyuan Zou
Zixuan Gu
Yuanqin He
Hideaki Takahashi
Yang Liu
Ya-Qin Zhang
FedML
323
15
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15 Oct 2023
Eliminating Label Leakage in Tree-Based Vertical Federated Learning
Hideaki Takahashi
Qingbin Liu
Yang Liu
AAML
FedML
334
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19 Jul 2023
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables
IEEE Transactions on Services Computing (IEEE TSC), 2023
Yifeng Zheng
Shuangqing Xu
Songlei Wang
Yan Gao
Zhongyun Hua
FedML
271
18
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22 May 2023
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates
Chenyang Ma
Xinchi Qiu
Daniel J. Beutel
Nicholas D. Lane
FedML
282
28
0
15 Apr 2023
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Qun Li
Chandra Thapa
Lawrence Ong
Yifeng Zheng
Hua Ma
S. Çamtepe
Anmin Fu
Yan Gao
FedML
309
15
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03 Feb 2023
Vertical Federated Learning: Concepts, Advances and Challenges
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Yang Liu
Weijing Chen
Tianyuan Zou
Yanhong Pu
Yuanqin He
Xiaozhou Ye
Ye Ouyang
Yaqin Zhang
Qian Yang
FedML
535
329
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23 Nov 2022
Coresets for Vertical Federated Learning: Regularized Linear Regression and
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Neural Information Processing Systems (NeurIPS), 2022
Lingxiao Huang
Zhize Li
Jialin Sun
Haoyu Zhao
FedML
249
22
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26 Oct 2022
Federated Boosted Decision Trees with Differential Privacy
Conference on Computer and Communications Security (CCS), 2022
Samuel Maddock
Graham Cormode
Tianhao Wang
Carsten Maple
S. Jha
FedML
252
46
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06 Oct 2022
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization
Proceedings of the VLDB Endowment (PVLDB), 2022
Xiaochen Li
Yuke Hu
Weiran Liu
Hanwen Feng
Li Peng
Yuan Hong
Kui Ren
Zhan Qin
FedML
319
39
0
04 Oct 2022
Federated XGBoost on Sample-Wise Non-IID Data
Katelinh Jones
Yuya Jeremy Ong
Yi Zhou
Nathalie Baracaldo
FedML
298
12
0
03 Sep 2022
Continual Horizontal Federated Learning for Heterogeneous Data
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Junki Mori
Isamu Teranishi
Ryo Furukawa
FedML
236
14
0
04 Mar 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning
Proceedings of the IEEE (Proc. IEEE), 2022
Chuan Ma
Jun Li
Kang Wei
Bo Liu
Ming Ding
Long Yuan
Zhu Han
H. Vincent Poor
441
77
0
18 Feb 2022
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction
Haizhou Liu
Xuan Zhang
Xinwei Shen
Hongbin Sun
FedML
200
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Enabling SQL-based Training Data Debugging for Federated Learning
Proceedings of the VLDB Endowment (PVLDB), 2021
Yejia Liu
Weiyuan Wu
Lampros Flokas
Jiannan Wang
Eugene Wu
FedML
164
16
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26 Aug 2021
PIVODL: Privacy-preserving vertical federated learning over distributed labels
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2021
Hangyu Zhu
Rui Wang
Yaochu Jin
K. Liang
FedML
286
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Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Jiabo He
Chen Chen
Lichao Sun
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Philip S. Yu
FedML
638
504
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Practical Privacy Attacks on Vertical Federated Learning
Haiqin Weng
Juntao Zhang
Jiabo He
Feng Xue
Tao Wei
S. Ji
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FedML
267
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Secure Collaborative Training and Inference for XGBoost
Andrew Law
Chester Leung
Rishabh Poddar
Raluca A. Popa
Chenyu Shi
Octavian Sima
Chaofan Yu
Xingmeng Zhang
Wenting Zheng
FedML
206
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06 Oct 2020
Privacy Preserving Vertical Federated Learning for Tree-based Models
Yuncheng Wu
Shaofeng Cai
Xiaokui Xiao
Gang Chen
Beng Chin Ooi
FedML
208
255
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Privacy-Preserving Gradient Boosting Decision Trees
AAAI Conference on Artificial Intelligence (AAAI), 2019
Yue Liu
Zhaomin Wu
Zeyi Wen
Bingsheng He
326
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11 Nov 2019
Practical Federated Gradient Boosting Decision Trees
AAAI Conference on Artificial Intelligence (AAAI), 2019
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Zeyi Wen
Bingsheng He
FedML
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474
214
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11 Nov 2019
An Experimental Evaluation of Large Scale GBDT Systems
Proceedings of the VLDB Endowment (PVLDB), 2019
Fangcheng Fu
Jiawei Jiang
Yingxia Shao
Tengjiao Wang
230
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Cong Xie
Oluwasanmi Koyejo
Indranil Gupta
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Federated Machine Learning: Concept and Applications
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How To Backdoor Federated Learning
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