Reproducibility in Learning

Understand

We introduce the notion of a reproducible algorithm in the context of learning.

• A reproducible learning algorithm is resilient to variations in its samples -- with high probability, it returns the exact same output when run on two samples from the same underlying distribution.
• We begin by unpacking the definition, clarifying how randomness is instrumental in balancing accuracy and reproducibility.
• We initiate a theory of reproducible algorithms, showing how reproducibility implies desirable properties such as data reuse and efficient testability.