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01/20/2022
Minimax Demographic Group Fairness in Federated Learning
Federated learning is an increasingly popular paradigm that enables a la...
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12/20/2021
Distributionally Robust Group Backwards Compatibility
Machine learning models are updated as new data is acquired or new archi...
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10/05/2021
Federating for Learning Group Fair Models
Federated learning is an increasingly popular paradigm that enables a la...
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11/03/2020
Minimax Pareto Fairness: A Multi Objective Perspective
In this work we formulate and formally characterize group fairness as a ...
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11/02/2020
Instance based Generalization in Reinforcement Learning
Agents trained via deep reinforcement learning (RL) routinely fail to ge...
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11/16/2019
Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare
Common fairness definitions in machine learning focus on balancing notio...
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02/14/2019
Non-contact photoplethysmogram and instantaneous heart rate estimation from infrared face video
Extracting the instantaneous heart rate (iHR) from face videos has been ...
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05/18/2018
