The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications ... machine ...

These are the building blocks of shapes ... known Fano varieties. Machine learning, however, is built to find patterns in large datasets. By training a machine learning model with some example ...

The intersection of machine learning and mathematical logic — spanning computer science ... Freitag discussed Littlestone dimension and its origins in model theory. He also connected trees and ...

Kraska’s team developed an algorithm that can also apply this kind of logic. They called it a “learned Bloom filter,” and it combines a small Bloom filter with a recurrent neural network (RNN) — a ...

“Essentially you download it, you write down your model or your knowledge or whatever assumptions your making in first-order logic,” he says. “And then you learn weights, and now you have a machine ...