13 citations · 42 across the 8 of their papers we have counts for
8 papers
VTarbel: Targeted Label Attack with Minimal Knowledge on Detector-enhanced Vertical Federated Learning
Juntao Tan, Anran Li, Quanchao Liu +2
Vertical federated learning (VFL) enables multiple parties with disjoint features to collaboratively train models without sharing raw data. While privacy vulnerabilities of VFL are…
Aggregating Intrinsic Information to Enhance BCI Performance through Federated Learning
Rui Liu, Yuanyuan Chen, Anran Li +3
Insufficient data is a long-standing challenge for Brain-Computer Interface (BCI) to build a high-performance deep learning model. Though numerous research groups and institutes co…
An Empirical Study on Noisy Label Learning for Program Understanding
Wenhan Wang, Yanzhou Li, Anran Li +3
Recently, deep learning models have been widely applied in program understanding tasks, and these models achieve state-of-the-art results on many benchmark datasets. A major challe…
Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization
James M. Dolezal, Sara Kochanny, Emma Dyer +6
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environment…
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning
Anran Li, Hongyi Peng, Lan Zhang +4
Vertical Federated Learning (VFL) enables multiple data owners, each holding a different subset of features about largely overlapping sets of data sample(s), to jointly train a use…
Towards Interpretable Federated Learning
Anran Li, Rui Liu, Ming Hu +4
Federated learning (FL) enables multiple data owners to build machine learning models collaboratively without exposing their private local data. In order for FL to achieve widespre…
Learning Program Representations with a Tree-Structured Transformer
Wenhan Wang, Kechi Zhang, Ge Li +4
Learning vector representations for programs is a critical step in applying deep learning techniques for program understanding tasks. Various neural network models are proposed to…
Residue-based Label Protection Mechanisms in Vertical Logistic Regression
Juntao Tan, Lan Zhang, Yang Liu +2
Federated learning (FL) enables distributed participants to collaboratively learn a global model without revealing their private data to each other. Recently, vertical FL, where th…