Fooling Partial Dependence via Data Poisoning

26 May 2021

Papers citing "Fooling Partial Dependence via Data Poisoning"

5 / 5 papers shown

Title
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution Eslam Zaher Maciej Trzaskowski Quan Nguyen Fred Roosta AAML 29 4 0 16 May 2024
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots Xi Xin Giles Hooker Fei Huang AAML 46 6 0 29 Apr 2024
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 40 3 0 07 Feb 2023
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Fool SHAP with Stealthily Biased Sampling Gabriel Laberge Ulrich Aïvodji Satoshi Hara M. Marchand Foutse Khomh MLAU AAML FAtt 10 2 0 30 May 2022