In the realm of machine learning, training accurate and robust models is a constant pursuit. However, two common challenges that often hinder model performance are overfitting and underfitting.

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning. This is something that holds great ...

Also: Google Next 2018: A deeper dive on AI and machine learning advances The paper explicitly draws upon work for more than a decade now on "graph neural networks." It also echoes some of the ...

The core product is a knowledge graph they claim has mapped “over ... they have released a short report about the state of the machine learning industry. The key slide I saw in the report ...

Year-to-date through September, Euclidean Fund I was up 9.8% net of fees and expenses in the context of the S&P 500 delivering a 10.6% total return, ...