Predictive Multiplicity in Classification

14 September 2019

Papers citing "Predictive Multiplicity in Classification"

24 / 24 papers shown

Title
Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest Jakob Schoeffer Maria De-Arteaga Jonathan Elmer 113 0 0 05 Apr 2025
Unique Rashomon Sets for Robust Active Learning Simon Nugyen Kentaro Hoffman Tyler H. McCormick 64 0 0 13 Mar 2025
The Curious Case of Arbitrariness in Machine Learning Prakhar Ganesh Afaf Taik G. Farnadi 59 2 0 28 Jan 2025
A Tale of Two Imperatives: Privacy and Explainability Supriya Manna Niladri Sett 91 0 0 30 Dec 2024
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 45 0 0 29 Oct 2024
Amazing Things Come From Having Many Good Models Cynthia Rudin Chudi Zhong Lesia Semenova Margo Seltzer Ronald E. Parr Jiachang Liu Srikar Katta Jon Donnelly Harry Chen Zachery Boner 26 23 0 05 Jul 2024
Efficient Exploration of the Rashomon Set of Rule Set Models Martino Ciaperoni Han Xiao A. Gionis 23 3 0 05 Jun 2024
Learning from Uncertain Data: From Possible Worlds to Possible Models Jiongli Zhu Su Feng Boris Glavic Babak Salimi 27 0 0 28 May 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 79 7 0 12 Feb 2024
Similarity of Neural Network Models: A Survey of Functional and Representational Measures Max Klabunde Tobias Schumacher M. Strohmaier Florian Lemmerich 47 64 0 10 May 2023
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models Chudi Zhong Zhi Chen Jiachang Liu Margo Seltzer Cynthia Rudin 33 11 0 28 Mar 2023
Learning When to Advise Human Decision Makers Gali Noti Yiling Chen 39 15 0 27 Sep 2022
Algorithmic Fairness in Business Analytics: Directions for Research and Practice Maria De-Arteaga Stefan Feuerriegel M. Saar-Tsechansky FaML 16 42 0 22 Jul 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 30 29 0 06 Jul 2022
Perspectives on Incorporating Expert Feedback into Model Updates Valerie Chen Umang Bhatt Hoda Heidari Adrian Weller Ameet Talwalkar 30 11 0 13 May 2022
Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity Kacper Sokol Meelis Kull J. Chan Flora D. Salim 15 6 0 14 Mar 2022
Margin-distancing for safe model explanation Tom Yan Chicheng Zhang 28 3 0 23 Feb 2022
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence Kacper Sokol Peter A. Flach 31 20 0 29 Dec 2021
Characterizing the risk of fairwashing Ulrich Aivodji Hiromi Arai Sébastien Gambs Satoshi Hara 18 27 0 14 Jun 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 48 651 0 20 Mar 2021
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 48 669 0 06 Nov 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 17 85 0 23 Jun 2020
On the Existence of Simpler Machine Learning Models Lesia Semenova Cynthia Rudin Ronald E. Parr 11 85 0 05 Aug 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 201 2,082 0 24 Oct 2016