19 citations · 21 across the 5 of their papers we have counts for
5 papers
Adapting Fairness Interventions to Missing Values
Raymond Feng, Flavio P. Calmon, Hao Wang
Missing values in real-world data pose a significant and unique challenge to algorithmic fairness. Different demographic groups may be unequally affected by missing data, and the s…
Sharp bounds on the price of bandit feedback for several models of mistake-bounded online learning
Raymond Feng, Jesse Geneson, Andrew Lee +1
We determine sharp bounds on the price of bandit feedback for several variants of the mistake-bound model. The first part of the paper presents bounds on the -input weak reinfor…
Prime Sums
Anupam Datta, Nir Elber, Raymond Feng +2
We study the properties of certain graphs involving the sums of primes. Their structure largely turns out to relate to the distribution of prime gaps and can be roughly seen in Cra…
Analyzing the Machine Learning Conference Review Process
David Tran, Alex Valtchanov, Keshav Ganapathy +4
Mainstream machine learning conferences have seen a dramatic increase in the number of participants, along with a growing range of perspectives, in recent years. Members of the mac…
An Open Review of OpenReview: A Critical Analysis of the Machine Learning Conference Review Process
David Tran, Alex Valtchanov, Keshav Ganapathy +4
Mainstream machine learning conferences have seen a dramatic increase in the number of participants, along with a growing range of perspectives, in recent years. Members of the mac…