3 citations · 7 across the 6 of their papers we have counts for
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cs.LG2023★ 1 cited
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning
Hideaki Takahashi
This paper introduces AIJack, an open-source library designed to assess security and privacy risks associated with the training and deployment of machine learning models. Amid the…
cs.LG2023★ 3 cited
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning
Tianyuan Zou, Zixuan Gu, Yu He +3
Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish coopera…
cs.LG2023★ 1 cited
Eliminating Label Leakage in Tree-Based Vertical Federated Learning
Hideaki Takahashi, Jingjing Liu, Yang Liu
Vertical federated learning (VFL) enables multiple parties with disjoint features of a common user set to train a machine learning model without sharing their private data. Tree-ba…