Machine learning (ML) techniques are increasingly prevalent in education...
Knowledge distillation has proven to be an effective technique in improv...
Variational Inference (VI) is a popular alternative to asymptotically ex...
While many areas of machine learning have benefited from the increasing
...
We investigate different methods for regularizing quantile regression wh...
We study the problem of finding equilibrium strategies in multi-agent ga...
Many existing fairness criteria for machine learning involve equalizing ...
We demonstrate how easy it is for modern machine-learned systems to viol...
We present pairwise metrics of fairness for ranking and regression model...
We show that many machine learning goals, such as improved fairness metr...
Classifiers can be trained with data-dependent constraints to satisfy
fa...
We consider the problem of improving fairness when one lacks access to a...
Given a classifier ensemble and a set of examples to be classified, many...
We propose learning flexible but interpretable functions that aggregate ...