Abstract: Inference capabilities of machine learning (ML) systems skyrocketed in recent years, now playing a pivotal role in various aspect of society. The goal in statistical learning is to use data ...

Abstract: In this paper, we provide an introduction to machine learning tasks that address important problems in genomic medicine. One of the goals of genomic medicine is to determine how variations ...

The seven companies listed here cover the realistic range of what a buyer will encounter in 2026: embedded ML teams that own ...

The world's first arena for predictive intelligence, Forge is a live environment where machine learning models compete on real-world problems and improve together, built on the thesis that the future ...

The Gabe Cube does have one huge redeeming factor even in the current market ...

ICML 2026 opens in Seoul on July 6 with a record 23,918 submissions — more than double last year — and a research program ...

Artificial intelligence is transforming how we live and work, from personalized recommendations to health care innovation.

I didn’t even realize that those were questions you could ask,” he says, “and then that there were philosophical disciplines ...

Alex Chen's adaptive execution framework, using reinforcement learning, cuts trading costs and improves market visibility.

Credit card fraud is a significant problem, with billions of dollars lost each year. Machine learning can be used to detect credit card fraud by identifying patterns that are indicative of fraudulent ...

Cook County's machine-learning tax model made assessments fairer, yet homeowner bills soared. The appeals system, not the algorithm, is the culprit.