1 citations · 2 across the 3 of their papers we have counts for
3 papers
Diversified Ensembling: An Experiment in Crowdsourced Machine Learning
Ira Globus-Harris, Declan Harrison, Michael Kearns +2
Crowdsourced machine learning on competition platforms such as Kaggle is a popular and often effective method for generating accurate models. Typically, teams vie for the most accu…
Multicalibration as Boosting for Regression
Ira Globus-Harris, Declan Harrison, Michael Kearns +2
We study the connection between multicalibration and boosting for squared error regression. First we prove a useful characterization of multicalibration in terms of a ``swap regret…
An Algorithmic Framework for Bias Bounties
Ira Globus-Harris, Michael Kearns, Aaron Roth
We propose and analyze an algorithmic framework for "bias bounties": events in which external participants are invited to propose improvements to a trained model, akin to bug bount…