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03/18/2022
Decision-Making under Miscalibration
ML-based predictions are used to inform consequential decisions about in...
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11/21/2021
On Fairness and Stability in Two-Sided Matchings
There are growing concerns that algorithms, which increasingly make or i...
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10/02/2021
Consider the Alternatives: Navigating Fairness-Accuracy Tradeoffs via Disqualification
In many machine learning settings there is an inherent tension between f...
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05/20/2021
Multi-group Agnostic PAC Learnability
An agnostic PAC learning algorithm finds a predictor that is competitive...
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11/26/2020
Outcome Indistinguishability
Prediction algorithms assign numbers to individuals that are popularly u...
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04/04/2020
Abstracting Fairness: Oracles, Metrics, and Interpretability
It is well understood that classification algorithms, for example, for d...
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04/03/2019
Preference-Informed Fairness
As algorithms are increasingly used to make important decisions pertaini...
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05/07/2018
Fine-grained Complexity Meets IP = PSPACE
In this paper we study the fine-grained complexity of finding exact and ...
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03/08/2018
Probably Approximately Metric-Fair Learning
We study fairness in machine learning. A learning algorithm, given a tra...
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03/08/2018
Fairness Through Computationally-Bounded Awareness
We study the problem of fair classification within the versatile framewo...
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11/22/2017
