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Beyond Static Classification: Long-term Fairness for Minority Groups via Performative Prediction and Distributionally Robust Optimization
DownloadFall 2022
In recent years machine learning (ML) models have begun to be deployed at enormous scales, but too often without adequate concern for whether or not an ML model will make fair decisions. Fairness in ML is a burgeoning research area, but work to define formal fairness criteria has some serious...
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Fall 2022
The motivation to incorporate planning, temporal abstraction and value function approximation in reinforcement learning (RL) algorithms is to reduce the amount of interaction with the environment needed to learn a near-optimal policy. Although each of these concepts has been under intense...
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Fall 2020
Over the coming decades, global population and energy consumption are projected to increase dramatically, with the latter doubling by 2050 as per the most conservative estimates. Much of this demand is likely to be met with increased use of fossil fuels. The burning of fossil fuels is a major...