Web: http://arxiv.org/abs/2201.11196

Jan. 28, 2022, 2:10 a.m. | Eldon Schoop, Ben Wedin, Andrei Kapishnikov, Tolga Bolukbasi, Michael Terry

cs.LG updates on arXiv.org arxiv.org

Developing a suitable Deep Neural Network (DNN) often requires significant
iteration, where different model versions are evaluated and compared. While
metrics such as accuracy are a powerful means to succinctly describe a model's
performance across a dataset or to directly compare model versions,
practitioners often wish to gain a deeper understanding of the factors that
influence a model's predictions. Interpretability techniques such as
gradient-based methods and local approximations can be used to examine small
sets of inputs in fine detail, …

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