A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

But unlike most quants, I run a concentrated, fundamentals-based portfolio. More than 50% of my fund is invested in only eight companies, and they're the kinds of stocks that Peter Lynch and Charlie ...

Earlier this year when a UK Treasury Committee released a report warning that regulators’ complacency on AI in financial ...

Machine learning algorithms create potentially more accurate models than linear models, but any increase in accuracy over more traditional, better-understood, and more easily explainable techniques is ...

Breast cancer diagnosis relies on imaging, yet conventional Doppler ultrasound possesses limitations in visualizing tumor microvasculature. This study aimed to compare Microvascular Flow imaging ...

This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with.

We use positive and unlabeled (PU) learning to address this challenge. Objective: This study aims to identify US Veterans whose self-harm events were not explicitly captured through diagnostic codes ...

For example, GBDT may automatically identify that the combination of “high HII and low GCS” significantly increases the risk of rebleeding, whereas in traditional logistic regression, such an ...