Abstract: Machine learning (ML) is ever more frequently used as ... In this article we propose the use of binary decision diagrams (BDDs) as an interpretable ML model. BDDs can be deemed as ...

Cluster Boost harnesses the strengths of both unsupervised and supervised learning methods, combining them to create a more robust and accurate predictive model. The proposed Cluster Boost model ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like ...

Designed to support the entire machine learning lifecycle -- from data ingestion and model training to deployment and monitoring -- Azure ML is empowering developers to integrate predictive ...

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve ...

Docling uses state-of-the-art models for layout analysis and table structure recognition to transform unstructured documents ...

Ivy: Dull dull dull dull dull dull dull dull dull dull dull dull dull. Posey: No, you're not. Ivy: Not me! The flowers. I planted all these carnations months ago and I thought they'd be colourful ...

Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine ...