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dateMore Than a Year Ago
subjectArtificial Intelligence
authorZachary C. Lipton
Research for Practice
From Communications of the ACM

Research for Practice: Troubling Trends in Machine-Learning Scholarship

Some ML papers suffer from flaws that could mislead the public and stymie future research. Zachary C. Lipton, Jacob Steinhardt
From Communications of the ACM | June 2019
The Mythos of Model Interpretability
From Communications of the ACM

The Mythos of Model Interpretability

In machine learning, the concept of interpretability is both important and slippery. Zachary C. Lipton
From Communications of the ACM | October 2018
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