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09/08/2022
Lost in Translation: Reimagining the Machine Learning Life Cycle in Education
Machine learning (ML) techniques are increasingly prevalent in education...
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06/13/2022
Robust Distillation for Worst-class Performance
Knowledge distillation has proven to be an effective technique in improv...
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06/30/2021
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence
Variational Inference (VI) is a popular alternative to asymptotically ex...
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03/30/2021
Multi-Source Causal Inference Using Control Variates
While many areas of machine learning have benefited from the increasing ...
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02/09/2021
Regularization Strategies for Quantile Regression
We investigate different methods for regularizing quantile regression wh...
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07/10/2020
Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty
We study the problem of finding equilibrium strategies in multi-agent ga...
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02/21/2020
Robust Optimization for Fairness with Noisy Protected Groups
Many existing fairness criteria for machine learning involve equalizing ...
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01/31/2020
Deontological Ethics By Monotonicity Shape Constraints
We demonstrate how easy it is for modern machine-learned systems to viol...
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06/12/2019
Pairwise Fairness for Ranking and Regression
We present pairwise metrics of fairness for ranking and regression model...
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09/11/2018
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
We show that many machine learning goals, such as improved fairness metr...
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06/29/2018
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Classifiers can be trained with data-dependent constraints to satisfy fa...
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06/28/2018
Proxy Fairness
We consider the problem of improving fairness when one lacks access to a...
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06/28/2018
Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization
Given a classifier ensemble and a set of examples to be classified, many...
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05/31/2018
