Browsing University of Waterloo by Subject "interpretability"
Now showing items 1-3 of 3
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Class Based Strategies for Understanding Neural Networks
(University of Waterloo, 2020-02-07)One of the main challenges for broad adoption of deep learning based models such as Convolutional Neural Networks (CNN), is the lack of understanding of their decisions. In many applications, a simpler, less capable model ... -
Less is More: Restricted Representations for Better Interpretability and Generalizability
(University of Waterloo, 2023-08-22)Deep neural networks are prevalent in supervised learning for large amounts of tasks such as image classification, machine translation and even scientific discovery. Their success is often at the sacrifice of interpretability ... -
Trade-Offs between Fairness, Interpretability, and Privacy in Machine Learning
(University of Waterloo, 2020-05-14)Algorithms have increasingly been deployed to make consequential decisions, and there have been many ethical questions raised about how these algorithms function. Three ethical considerations we look at in this work are ...