A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...

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 ...

UTokyo and Kubota develop a drone potato yield prediction method combining multispectral imagery, AI, and growth models.

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

Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...

Managing a medical supply chain in low- and middle-income countries can mean navigating a landscape prone to extreme and ...

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

Introduces a low-rank-based approach to KV cache compression, one of the key bottlenecks in long-context AISpeeds up attention computation by up to 6.9x and overall generation throughput by up to 3.1x ...

KV, a low-rank KV cache compression method achieving up to 20x reduction, with the paper selected as a Spotlight at ICML 2026 ...