Tagged articles

vertical federated learning

4 articles · Page 1 of 1

Oct 22, 2026 · Artificial Intelligence

Data Stays, Model Moves: SDH PaaS 3.0's Federated Learning Productization

SDH PaaS 3.0 integrates vertical federated learning into data collaboration workflows, enabling platform and business parties to jointly train conversion prediction models without sharing raw data, covering role assignment, sample alignment, encrypted intermediate exchange, privacy controls, task orchestration with approvals, and engineering optimizations for large-scale stability.

SDH PaaS 3.0conversion predictiondata collaboration

0 likes · 15 min read

Data Stays, Model Moves: SDH PaaS 3.0's Federated Learning Productization

Machine Heart

Apr 15, 2026 · Artificial Intelligence

When Usability Becomes a Weakness: How VENOM Breaks Vertical Federated Learning

The paper reveals that intermediate representations in vertical federated learning retain exploitable geometric structure, and introduces VENOM—a geometry‑aware model‑stealing framework that outperforms existing defenses across multiple datasets, even under distribution shift.

AI securityVENOMgeometry-based attack

0 likes · 6 min read

When Usability Becomes a Weakness: How VENOM Breaks Vertical Federated Learning

Tencent Advertising Technology

Oct 23, 2024 · Artificial Intelligence

FedMix: Boosting Vertical Federated Learning with Data Mixture

This paper introduces FedMix, a method that enhances vertical federated learning by mixing aligned and unaligned data, theoretically demonstrating the value of unaligned data and empirically achieving over 10% ROI improvement and significant AUC gains while keeping computational and communication overhead low.

data mixturefederated learningprivacy

0 likes · 11 min read

FedMix: Boosting Vertical Federated Learning with Data Mixture

WeChat Backend Team

Jun 13, 2023 · Artificial Intelligence

Boosting Vertical Federated Learning: Optimizing Paillier Encryption & Model Stability

This article examines the challenges of data privacy in big‑data environments and presents a comprehensive approach to vertical federated learning, detailing framework optimizations, Paillier homomorphic encryption enhancements, PSI‑based feature selection, and adversarial learning techniques to improve model stability and deployment on a unified ML platform.

Machine LearningModel StabilityPaillier encryption

0 likes · 19 min read

Boosting Vertical Federated Learning: Optimizing Paillier Encryption & Model Stability