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08/24/2023
Prediction without Preclusion: Recourse Verification with Reachable Sets
Machine learning models are often used to decide who will receive a loan...
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05/15/2023
Algorithmic Censoring in Dynamic Learning Systems
Dynamic learning systems subject to selective labeling exhibit censoring...
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02/08/2023
Participatory Systems for Personalized Prediction
Machine learning models are often personalized based on information that...
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06/04/2022
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction
The standard approach to personalization in machine learning consists of...
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06/02/2022
Predictive Multiplicity in Probabilistic Classification
For a prediction task, there may exist multiple models that perform almo...
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12/02/2021
Learning Optimal Predictive Checklists
Checklists are simple decision aids that are often used to promote safet...
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09/14/2019
Predictive Multiplicity in Classification
In the context of machine learning, a prediction problem exhibits predic...
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01/29/2019
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
When the average performance of a prediction model varies significantly ...
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09/18/2018
Actionable Recourse in Linear Classification
Classification models are often used to make decisions that affect human...
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01/16/2018
On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning
In the context of machine learning, disparate impact refers to a form of...
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10/01/2016
Learning Optimized Risk Scores on Large-Scale Datasets
Risk scores are simple classification models that let users quickly asse...
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03/26/2015
Interpretable Classification Models for Recidivism Prediction
We investigate a long-debated question, which is how to create predictiv...
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02/15/2015
Supersparse Linear Integer Models for Optimized Medical Scoring Systems
Scoring systems are linear classification models that only require users...
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05/16/2014
Methods and Models for Interpretable Linear Classification
We present an integer programming framework to build accurate and interp...
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06/27/2013
Supersparse Linear Integer Models for Interpretable Classification
Scoring systems are classification models that only require users to add...
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06/25/2013
