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02/09/2023
Symbolic Metamodels for Interpreting Black-boxes Using Primitive Functions
One approach for interpreting black-box machine learning models is to fi...
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02/24/2022
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift
A common assumption in semi-supervised learning is that the labeled, unl...
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10/26/2021
Fair Sequential Selection Using Supervised Learning Models
We consider a selection problem where sequentially arrived applicants ap...
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01/26/2021
RewardRating: A Mechanism Design Approach to Improve Rating Systems
Nowadays, rating systems play a crucial role in the attraction of custom...
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12/07/2020
Improving Fairness and Privacy in Selection Problems
Supervised learning models have been increasingly used for making decisi...
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10/08/2019
Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms
Alternating direction method of multiplier (ADMM) is a powerful method t...
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05/02/2019
Long term impact of fair machine learning in sequential decision making: representation disparity and group retention
Machine learning models trained on data from multiple demographic groups...
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10/07/2018
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms
Alternating direction method of multiplier (ADMM) is a powerful method t...
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06/06/2018