Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

Leaf functional traits—chlorophyll (CHL), carotenoid (CAR), equivalent water thickness (EWT), nitrogen (N), and leaf mass per ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

Abstract: In this letter, we consider the concept of mobile crowd-machine learning (MCML) for a federated learning model. The MCML enables mobile devices in a mobile network to collaboratively train ...

Graduates of the CUNY Graduate Center's Ph.D. program in Computer Science become masters of the computer science discipline and obtain in-depth knowledge of a specialized area. CUNY Graduate Center Ph ...

This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.

Abstract: This study proposes a machine learning based methodology for estimating Arctic thin sea ice thickness (up to 1 m) from brightness temperature measurements of SMOS. The approach involves ...

Experiment with science, art, technology, and delightful ideas. The Tinkering Studio is primarily an R&D laboratory, so whenever possible we try to share our projects, explorations, and developing ...

On good days, the world seems like a well-run railway: things happen according to principles, laws, rules and generalisations that we humans understand and can apply to particulars. We forgive the ...

Using a machine-learning, data-driven algorithm, we identified that a combination of age, fever, and tachypnea was the most parsimonious predictor of ICU admission; patients younger than 56 years, ...

SAN FRANCISCO (Reuters) - Amazon.com Inc's machine-learning specialists uncovered a big problem: their new recruiting engine did not like women. The team had been building computer programs since 2014 ...