Programs as Black-Box Explanations

  title={Programs as Black-Box Explanations},
  author={Sameer Singh and Marco T{\'u}lio Ribeiro and Carlos Guestrin},
With increasing complexity of machine learning systems being used1, there is a crucial need for providing insights into what these models are doing. Model-agnostic approaches [18], such as Baehrens et al. [1] and Ribeiro et al. [17], have shown that insights into complex, black-box models do not have to come at a cost of accuracy, and that accurate local explanations can successfully be provided for a number of complex classifiers (such as random forests and deep neural networks) and domains… CONTINUE READING

4 Figures & Tables



Citations per Year

Citation Velocity: 6

Averaging 6 citations per year over the last 2 years.

Learn more about how we calculate this metric in our FAQ.