User Driven Model Adjustment via Boolean Rule Explanations

User Driven Model Adjustment via Boolean Rule Explanations

28 March 2022

Elizabeth M. Daly

Massimiliano Mattetti

Papers citing "User Driven Model Adjustment via Boolean Rule Explanations"

9 / 9 papers shown

Title
Toward Machine-Guided, Human-Initiated Explanatory Interactive Learning Teodora Popordanoska Mohit Kumar Stefano Teso 34 1 0 20 Jul 2020
Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience Bhavya Ghai Q. V. Liao Yunfeng Zhang Rachel K. E. Bellamy Klaus Mueller 44 29 0 24 Jan 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations P. Schramowski Wolfgang Stammer Stefano Teso Anna Brugger Xiaoting Shao Hans-Georg Luigs Anne-Katrin Mahlein Kristian Kersting 74 207 0 15 Jan 2020
Auditing and Debugging Deep Learning Models via Decision Boundaries: Individual-level and Group-level Analysis Roozbeh Yousefzadeh D. O’Leary AAML FAtt 29 5 0 03 Jan 2020
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind ... Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis L. Wei Yunfeng Zhang XAI 26 391 0 06 Sep 2019
Boolean Decision Rules via Column Generation S. Dash Oktay Gunluk Dennis L. Wei 47 174 0 24 May 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 91 587 0 21 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 83 3,922 0 06 Feb 2018
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 587 16,828 0 16 Feb 2016