1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2018
Feature-Wise Bias Amplification
Klas Leino, Emily Black, Matt Fredrikson +2
We study the phenomenon of bias amplification in classifiers, wherein a machine learning model learns to predict classes with a greater disparity than the underlying ground truth.…
cs.AI2017★ 1 cited
Case Study: Explaining Diabetic Retinopathy Detection Deep CNNs via Integrated Gradients
Linyi Li, Matt Fredrikson, Shayak Sen +1
In this report, we applied integrated gradients to explaining a neural network for diabetic retinopathy detection. The integrated gradient is an attribution method which measures t…
cs.LG2016
Debugging Machine Learning Tasks
Aleksandar Chakarov, Aditya Nori, Sriram Rajamani +2
Unlike traditional programs (such as operating systems or word processors) which have large amounts of code, machine learning tasks use programs with relatively small amounts of co…