Machine learning is interpolative

In most applications, machine learning models, such as simple feedforward networks perform inference by interpolating the latent space derived through training. Therefore, those models have trouble generalizing beyond the domain of training data. Program synthesis, in contrast, attempts to generalize through extrapolation.

Resources

Backlinks