7 citations · 12 across the 6 of their papers we have counts for
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cs.LG2022★ 7 cited
A General Framework for Auditing Differentially Private Machine Learning
Fred Lu, Joseph Munoz, Maya Fuchs +5
We present a framework to statistically audit the privacy guarantee conferred by a differentially private machine learner in practice. While previous works have taken steps toward…
cs.LG2022★ 3 cited
Neural Bregman Divergences for Distance Learning
Fred Lu, Edward Raff, Francis Ferraro
Many metric learning tasks, such as triplet learning, nearest neighbor retrieval, and visualization, are treated primarily as embedding tasks where the ultimate metric is some vari…
cs.LG2022
Continuously Generalized Ordinal Regression for Linear and Deep Models
Fred Lu, Francis Ferraro, Edward Raff
Ordinal regression is a classification task where classes have an order and prediction error increases the further the predicted class is from the true class. The standard approach…