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06/12/2023
Gaussian Membership Inference Privacy
We propose a new privacy notion called f-Membership Inference Privacy (f...
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11/10/2022
On the Privacy Risks of Algorithmic Recourse
As predictive models are increasingly being employed to make consequenti...
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11/03/2022
Decomposing Counterfactual Explanations for Consequential Decision Making
The goal of algorithmic recourse is to reverse unfavorable decisions (e....
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10/25/2022
I Prefer not to Say: Operationalizing Fair and User-guided Data Minimization
To grant users greater authority over their personal data, policymakers ...
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08/30/2022
On the Trade-Off between Actionable Explanations and the Right to be Forgotten
As machine learning (ML) models are increasingly being deployed in high-...
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06/22/2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations
While several types of post hoc explanation methods (e.g., feature attri...
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03/14/2022
Rethinking Stability for Attribution-based Explanations
As attribution-based explanation methods are increasingly used to establ...
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03/13/2022
Algorithmic Recourse in the Face of Noisy Human Responses
As machine learning (ML) models are increasingly being deployed in high-...
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08/02/2021
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Counterfactual explanations provide means for prescriptive model explana...
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06/18/2021
On the Connections between Counterfactual Explanations and Adversarial Examples
Counterfactual explanations and adversarial examples have emerged as cri...
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02/02/2021
Gaussian Experts Selection using Graphical Models
Local approximations are popular methods to scale Gaussian processes (GP...
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06/23/2020
On Counterfactual Explanations under Predictive Multiplicity
Counterfactual explanations are usually obtained by identifying the smal...
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06/18/2020
Leveraging Model Inherent Variable Importance for Stable Online Feature Selection
Feature selection can be a crucial factor in obtaining robust and accura...
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10/21/2019
