In today’s fast-paced digital environment, businesses are under constant pressure to improve conversion rates and create more personalized user experiences. With traditional conversion optimization ...

Efficient Training of Infinite-depth Neural Networks via Jacobian-free Backpropagation A promising trend in deep learning replaces fixed depth models by approximations of the limit as network depth ...

Optimization and statistics are everywhere, touching all engineering disciplines in an ever more sophisticated way. Nowhere are they more important than in the rapidly evolving field of machine ...

In this article I demonstrate how to use evolutionary optimization to train a logistic regression model. Along the way, I'll explain how to adapt the example to other types of machine learning models.

While a machine today could be readily taught that difference by being shown lots of examples ... deep learning systems can reason about the world in terms of semantics, rather than statistics ...

"What's the difference between mathematical optimization and machine learning?" This is a question ... both are based on deep mathematics and are shining examples of how mathematics — along ...

We hear about applications of machine learning on a daily basis, although not all of them are unalloyed successes. Self-driving cars are a good example, where tasks range from simple and ...

In today’s data-driven world, the ability to efficiently scale machine learning (ML) models and optimize their ... Advanced feature engineering, combined with ML optimization techniques, plays a vital ...