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Tree-based Models for Vertical Federated Learning: A Survey
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-63076-8_17openalex-snapshot
Federated Learning for Open Banking
inferredcites →https://doi.org/10.1007/978-3-030-63076-8_5openalex-snapshot
Large-Scale Kernel Method for Vertical Federated Learning
inferredcites →https://doi.org/10.1007/978-3-030-96896-0_2openalex-snapshot
Tree-Based Models for Federated Learning Systems
inferredcites →https://doi.org/10.1007/978-3-540-79228-4_1openalex-snapshot
Differential Privacy: A Survey of Results
inferredcites →https://doi.org/10.1007/978-3-642-39077-7_5openalex-snapshot
Broadening the Scope of Differential Privacy Using Metrics
inferredcites →https://doi.org/10.1016/j.csi.2023.103827openalex-snapshot
Local differential privacy and its applications: A comprehensive survey
inferredcites →https://doi.org/10.1016/j.ins.2018.10.024openalex-snapshot
Secure Multi-Party Computation: Theory, practice and applications
inferredcites →https://doi.org/10.1016/j.jnca.2018.05.003openalex-snapshot
Distributed learning of deep neural network over multiple agents
inferredcites →https://doi.org/10.1016/j.scs.2021.103663openalex-snapshot
Federated learning enabled digital twins for smart cities: Concepts, recent advances, and future directions
inferredcites →https://doi.org/10.1049/cim2.12057openalex-snapshot
Privacy‐preserving gradient boosting tree: Vertical federated learning for collaborative bearing fault diagnosis
inferredcites →https://doi.org/10.1080/09540091.2021.1936455openalex-snapshot
Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges
inferredcites →https://doi.org/10.1109/21.97458openalex-snapshot
A survey of decision tree classifier methodology
inferredcites →https://doi.org/10.1109/access.2020.3013541openalex-snapshot
Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications
inferredcites →https://doi.org/10.1109/comst.2020.2986024openalex-snapshot
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/csf43763.2018openalex-snapshot
2018 IEEE 31st Computer Security Foundations Symposium (CSF)
inferredcites →https://doi.org/10.1109/eiecs53707.2021openalex-snapshot
2021 International Conference on Electronic Information Engineering and Computer Science (EIECS)
inferredcites →https://doi.org/10.1109/icct52962.2021.9657870openalex-snapshot
Federated Learning Application on Telecommunication-Joint Healthcare Recommendation
inferredcites →https://doi.org/10.1109/jiot.2019.2952146openalex-snapshot
Local Differential Privacy for Deep Learning
inferredcites →https://doi.org/10.1109/mis.2021.3082561openalex-snapshot
SecureBoost: A Lossless Federated Learning Framework
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/tdsc.2023.3276365openalex-snapshot
${\sf FederBoost}$: Private Federated Learning for GBDT
inferredcites →https://doi.org/10.1109/tifs.2022.3231784openalex-snapshot
PriVDT: An Efficient Two-Party Cryptographic Framework for Vertical Decision Trees
inferredcites →https://doi.org/10.1109/tifs.2022.3232955openalex-snapshot
SGBoost: An Efficient and Privacy-Preserving Vertical Federated Tree Boosting Framework
inferredcites →https://doi.org/10.1109/tii.2022.3148997openalex-snapshot
A Secure Cloudlet-Based Charging Station Recommendation for Electric Vehicles Empowered by Federated Learning
inferredcites →https://doi.org/10.1109/tkde.2021.3124599openalex-snapshot
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
inferredcites →https://doi.org/10.1109/trustcom.2015.357openalex-snapshot
Trusted Execution Environment: What It is, and What It is Not
inferredcites →https://doi.org/10.1109/tsc.2023.3279839openalex-snapshot
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables
inferredcites →https://doi.org/10.1109/tsc.2024.3394706openalex-snapshot
ELXGB: An Efficient and Privacy-Preserving XGBoost for Vertical Federated Learning
inferredcites →https://doi.org/10.1109/tsmcc.2004.843247openalex-snapshot
Top-Down Induction of Decision Trees Classifiers—A Survey
inferredcites →https://doi.org/10.1126/science.1127647openalex-snapshot
Reducing the Dimensionality of Data with Neural Networks
inferredcites →https://doi.org/10.1126/science.aaa8415openalex-snapshot
Machine learning: Trends, perspectives, and prospects
inferredcites →https://doi.org/10.1145/1315245openalex-snapshot
Proceedings of the 14th ACM conference on Computer and communications security
inferredcites →https://doi.org/10.1145/1536414.1536440openalex-snapshot
Fully homomorphic encryption using ideal lattices
inferredcites →https://doi.org/10.1145/2046660.2046682openalex-snapshot
Can homomorphic encryption be practical?
inferredcites →https://doi.org/10.1145/2508859.2516701openalex-snapshot
When private set intersection meets big data
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3109859.3109881openalex-snapshot
Secure Multi-Party Protocols for Item-Based Collaborative Filtering
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3133956.3134061openalex-snapshot
Fast Private Set Intersection from Homomorphic Encryption
inferredcites →https://doi.org/10.1145/3154794openalex-snapshot
Scalable Private Set Intersection Based on OT Extension
inferredcites →https://doi.org/10.1145/3214303openalex-snapshot
A Survey on Homomorphic Encryption Schemes
inferredcites →https://doi.org/10.1145/3299869openalex-snapshot
Proceedings of the 2019 International Conference on Management of Data
inferredcites →https://doi.org/10.1145/3339474openalex-snapshot
Comparison and Modelling of Country-level Microblog User and Activity in Cyber-physical-social Systems Using Weibo and Twitter Data
inferredcites →https://doi.org/10.1145/3387107openalex-snapshot
Federated learning for privacy-preserving AI
inferredcites →https://doi.org/10.1145/3394486.3403298openalex-snapshot
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
inferredcites →https://doi.org/10.1145/3447548.3467210openalex-snapshot
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control
inferredcites →https://doi.org/10.1145/3459637.3482361openalex-snapshot
Large-scale Secure XGB for Vertical Federated Learning
inferredcites →https://doi.org/10.1145/3523061openalex-snapshot
An Efficient Learning Framework for Federated XGBoost Using Secret Sharing and Distributed Optimization
inferredcites →https://doi.org/10.1145/3576915openalex-snapshot
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
inferredcites →https://doi.org/10.1145/3634737.3657024openalex-snapshot
SiGBDT: Large-Scale Gradient Boosting Decision Tree Training via Function Secret Sharing
inferredcites →https://doi.org/10.1145/366173openalex-snapshot
Proceedings of the 2000 workshop on New security paradigms
inferredcites →https://doi.org/10.1145/3720539openalex-snapshot
Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey
inferredcites →https://doi.org/10.1145/945445openalex-snapshot
Proceedings of the nineteenth ACM symposium on Operating systems principles
inferredcites →https://doi.org/10.1155/2007/13801openalex-snapshot
A Survey of Homomorphic Encryption for Nonspecialists
inferredcites →https://doi.org/10.11919/j.issn.1002-0829.215044openalex-snapshot
Decision tree methods: applications for classification and prediction.
inferredcites →https://doi.org/10.1201/9781315139470openalex-snapshot
Classification And Regression Trees
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.14778/3407790.3407811openalex-snapshot
Privacy preserving vertical federated learning for tree-based models
inferredcites →https://doi.org/10.14778/3579075.3579081openalex-snapshot
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1561/2200000083openalex-snapshot
Advances and Open Problems in Federated Learning
inferredcites →https://doi.org/10.1561/3300000019openalex-snapshot
A Pragmatic Introduction to Secure Multi-Party Computation
inferredcites →https://doi.org/10.21275/v5i4.nov162954openalex-snapshot
A Survey on Decision Tree Algorithms of Classification in Data Mining
inferredcites →https://doi.org/10.2478/popets-2021-0043openalex-snapshot
SoK: Privacy-Preserving Collaborative Tree-based Model Learning
inferredcites →https://doi.org/10.24963/ijcai.2022/272openalex-snapshot
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
inferredcites →https://doi.org/10.3390/risks7010029openalex-snapshot
Machine Learning in Banking Risk Management: A Literature Review
inferredcites →https://doi.org/10.3390/s20216230openalex-snapshot
Federated Learning in Smart City Sensing: Challenges and Opportunities
inferredcites →https://doi.org/10.48550/arxiv.1711.10677openalex-snapshot
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
inferredcites →https://doi.org/10.48550/arxiv.1810.11363openalex-snapshot
CatBoost: gradient boosting with categorical features support
inferredcites →https://doi.org/10.48550/arxiv.1901.09888openalex-snapshot
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
inferredcites →https://doi.org/10.48550/arxiv.1911.09824openalex-snapshot
Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator
inferredcites →https://doi.org/10.48550/arxiv.2007.06081openalex-snapshot
VAFL: a Method of Vertical Asynchronous Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2007.14390openalex-snapshot
Flower: A Friendly Federated Learning Research Framework
inferredcites →https://doi.org/10.48550/arxiv.2007.14513openalex-snapshot
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
inferredcites →https://doi.org/10.48550/arxiv.2104.00489openalex-snapshot
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
inferredcites →https://doi.org/10.48550/arxiv.2201.10761openalex-snapshot
An Efficient and Robust System for Vertically Federated Random Forest
inferredcites →https://doi.org/10.48550/arxiv.2202.07253openalex-snapshot
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2204.00976openalex-snapshot
FedGBF: An efficient vertical federated learning framework via gradient boosting and bagging
inferredcites →https://doi.org/10.48550/arxiv.2210.01318openalex-snapshot
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization
inferredcites →https://doi.org/10.48550/arxiv.2304.01829openalex-snapshot
A Survey on Vertical Federated Learning: From a Layered Perspective
inferredcites →https://doi.org/10.48550/arxiv.2402.03688openalex-snapshot
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
inferredcites →https://doi.org/10.5555/2907333.2907524openalex-snapshot
A Survey of Homomorphic Encryption for Nonspecialists
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-95-8056-9_28openalex-snapshot
The Nucleolus Solution for Data Valuation in Vertical Federated Learning-Based Mobility-as-a-Service Platforms
inferred← citeshttps://doi.org/10.1007/978-981-95-9113-8_31openalex-snapshot
Application of Machine Learning for Condominium Price Prediction Using Real-Time Web Scraped Data: Evidence from Hanoi’s Emerging Market
inferred← citeshttps://doi.org/10.1007/s10462-026-11555-0openalex-snapshot
Survey of privacy preserving federated tree-based learning
inferred← citeshttps://doi.org/10.1007/s10586-026-06286-4openalex-snapshot
A review of federated learning: architectures, challenges, and targeted solutions
inferred← citeshttps://doi.org/10.1007/s11280-026-01438-3openalex-snapshot
LISS: Defending against label inference attacks in VFL via secret subsampling
inferred← citeshttps://doi.org/10.1016/j.indic.2026.101525openalex-snapshot
Quantifying the spatiotemporal dynamics and drivers of urban blue spaces in the Beijing–Tianjin–Hebei region using remote sensing
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.117129openalex-snapshot
An Interpretable Vertical Federated Learning Framework Based on Belief Rule Bases for Long-Tailed Classification
inferred← citeshttps://doi.org/10.1109/iccci70321.2026.11666546openalex-snapshot
Conformal Label-Transition Auditing Against Label-Flipping Attacks in Trust-Aware Federated Learning
inferred← citeshttps://doi.org/10.1109/icts67612.2025.11369513openalex-snapshot
From Breakfast to Prediction: Unveiling Nasi Kuning Sales Patterns with Machine Learning
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3626379openalex-snapshot
SXGB: Secure and Efficient Vertical Federated XGBoost via Trusted Execution Environments
inferred← citeshttps://doi.org/10.1145/3705328.3748024openalex-snapshot
Popularity‑Bias Vulnerability: Semi‑Supervised Label Inference Attack on Federated Recommender Systems
inferred← citeshttps://doi.org/10.1145/3770855.3818433openalex-snapshot
HIVE: Hierarchical Generation of Integrated and Varied Ensembles for Efficient Out-of-Distribution Generalization
inferred← citeshttps://doi.org/10.3390/jcp6030079openalex-snapshot
Vertical Federated XGBoost with Privacy Preservation via Secure Multiparty Computation
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