91 citations · 189 across the 18 of their papers we have counts for
18 papers
IPProtect: protecting the intellectual property of visual datasets during data valuation
Gursimran Singh, Chendi Wang, Ahnaf Tazwar +2
Data trading is essential to accelerate the development of data-driven machine learning pipelines. The central problem in data trading is to estimate the utility of a seller's data…
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning
Shiqi He, Qifan Yan, Feijie Wu +3
Federated learning (FL) is an effective technique to directly involve edge devices in machine learning training while preserving client privacy. However, the substantial communicat…
Revealing Unfair Models by Mining Interpretable Evidence
Mohit Bajaj, Lingyang Chu, Vittorio Romaniello +5
The popularity of machine learning has increased the risk of unfair models getting deployed in high-stake applications, such as justice system, drug/vaccination design, and medical…
Intrinsic Bias Identification on Medical Image Datasets
Shijie Zhang, Lanjun Wang, Lian Ding +3
Machine learning based medical image analysis highly depends on datasets. Biases in the dataset can be learned by the model and degrade the generalizability of the applications. Th…
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation
Saeed Ranjbar Alvar, Lanjun Wang, Jian Pei +1
Image-to-image translation models are shown to be vulnerable to the Membership Inference Attack (MIA), in which the adversary's goal is to identify whether a sample is used to trai…
Targeted Data Poisoning Attack on News Recommendation System by Content Perturbation
Xudong Zhang, Zan Wang, Jingke Zhao +1
News Recommendation System(NRS) has become a fundamental technology to many online news services. Meanwhile, several studies show that recommendation systems(RS) are vulnerable to…