T-COL: Generating Counterfactual Explanations for General User
Preferences on Variable Machine Learning Systems

T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems

28 September 2023

Shi Feng

Papers citing "T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems"

5 / 5 papers shown

Title
Robust Counterfactual Explanations in Machine Learning: A Survey Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni OffRL CML 23 10 0 02 Feb 2024
Counterfactual Explanations Using Optimization With Constraint Learning Donato Maragno Tabea E. Rober Ilker Birbil CML 47 10 0 22 Sep 2022
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations Barry Smyth Mark T. Keane CML 34 26 0 22 Jan 2021
Issues with post-hoc counterfactual explanations: a discussion Thibault Laugel Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki CML 104 44 0 11 Jun 2019
A Random Forest Guided Tour Gérard Biau Erwan Scornet AI4TS 139 2,721 0 18 Nov 2015