Berk Ustun | DeepAI

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Featured Co-authors

Yang Liu
344 publications
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David C. Parkes
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Flavio P. Calmon
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Katherine Heller
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Alexander Spangher
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Chirag Nagpal
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∙ 05/15/2023

Algorithmic Censoring in Dynamic Learning Systems

Dynamic learning systems subject to selective labeling exhibit censoring...

4 Jennifer Chien, et al. ∙

∙ 02/08/2023

Participatory Systems for Personalized Prediction

Machine learning models are often personalized based on information that...

0 Hailey James, et al. ∙

∙ 06/04/2022

When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction

The standard approach to personalization in machine learning consists of...

0 Vinith M. Suriyakumar, et al. ∙

∙ 06/02/2022

Predictive Multiplicity in Probabilistic Classification

For a prediction task, there may exist multiple models that perform almo...

0 Jamelle Watson-Daniels, et al. ∙

∙ 12/02/2021

Learning Optimal Predictive Checklists

Checklists are simple decision aids that are often used to promote safet...

5 Haoran Zhang, et al. ∙

∙ 09/14/2019

Predictive Multiplicity in Classification

In the context of machine learning, a prediction problem exhibits predic...

0 Charles T. Marx, et al. ∙

∙ 01/29/2019

Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions

When the average performance of a prediction model varies significantly ...

4 Hao Wang, et al. ∙

∙ 09/18/2018

Actionable Recourse in Linear Classification

Classification models are often used to make decisions that affect human...

0 Berk Ustun, et al. ∙

∙ 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...

0 Hao Wang, et al. ∙

∙ 10/01/2016

Learning Optimized Risk Scores on Large-Scale Datasets

Risk scores are simple classification models that let users quickly asse...

0 Berk Ustun, et al. ∙

∙ 03/26/2015

Interpretable Classification Models for Recidivism Prediction

We investigate a long-debated question, which is how to create predictiv...

0 Jiaming Zeng, et al. ∙

∙ 02/15/2015

Supersparse Linear Integer Models for Optimized Medical Scoring Systems

Scoring systems are linear classification models that only require users...

0 Berk Ustun, et al. ∙

∙ 05/16/2014

Methods and Models for Interpretable Linear Classification

We present an integer programming framework to build accurate and interp...

0 Berk Ustun, et al. ∙

∙ 06/27/2013

Supersparse Linear Integer Models for Interpretable Classification

Scoring systems are classification models that only require users to add...

0 Berk Ustun, et al. ∙

∙ 06/25/2013

Supersparse Linear Integer Models for Predictive Scoring Systems

We introduce Supersparse Linear Integer Models (SLIM) as a tool to creat...

0 Berk Ustun, et al. ∙