most citedThreshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation

5 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DS2024

Efficient Data Shapley for Weighted Nearest Neighbor Algorithms

Jiachen T. Wang, Prateek Mittal, Ruoxi Jia

This work aims to address an open problem in data valuation literature concerning the efficient computation of Data Shapley for weighted nearest neighbor algorithm (WKNN-Shaple…

cs.LG20235 cited

Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation

Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang +2

Data valuation aims to quantify the usefulness of individual data sources in training machine learning (ML) models, and is a critical aspect of data-centric ML research. However, d…

cs.CR20234 cited

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection

Tinghao Xie, Xiangyu Qi, Ping He +3

We present a novel defense, against backdoor attacks on Deep Neural Networks (DNNs), wherein adversaries covertly implant malicious behaviors (backdoors) into DNNs. Our defense fal…

stat.ML2023

A Note on "Towards Efficient Data Valuation Based on the Shapley Value''

Jiachen T. Wang, Ruoxi Jia

The Shapley value (SV) has emerged as a promising method for data valuation. However, computing or estimating the SV is often computationally expensive. To overcome this challenge,…

cs.LG2023

Uncovering Adversarial Risks of Test-Time Adaptation

Tong Wu, Feiran Jia, Xiangyu Qi +4

Recently, test-time adaptation (TTA) has been proposed as a promising solution for addressing distribution shifts. It allows a base model to adapt to an unforeseen distribution dur…