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Learning Models for Actionable Recourse

Learning Models for Actionable Recourse

12 November 2020
Alexis Ross
Himabindu Lakkaraju
Osbert Bastani
    FaML
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Papers citing "Learning Models for Actionable Recourse"

3 / 3 papers shown
Title
Don't Lie to Me! Robust and Efficient Explainability with Verified
  Perturbation Analysis
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis
Thomas Fel
Mélanie Ducoffe
David Vigouroux
Rémi Cadène
Mikael Capelle
C. Nicodeme
Thomas Serre
AAML
23
41
0
15 Feb 2022
On the Adversarial Robustness of Causal Algorithmic Recourse
On the Adversarial Robustness of Causal Algorithmic Recourse
Ricardo Dominguez-Olmedo
Amir-Hossein Karimi
Bernhard Schölkopf
46
63
0
21 Dec 2021
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Sangdon Park
Osbert Bastani
Nikolai Matni
Insup Lee
UQCV
136
68
0
31 Dec 2019
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