7 citations · 22 across the 18 of their papers we have counts for
4 papers · 1 filter
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…
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…
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks
Andre T. Nguyen, Fred Lu, Gary Lopez Munoz +3
We explore the utility of information contained within a dropout based Bayesian neural network (BNN) for the task of detecting out of distribution (OOD) data. We first show how pre…
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…