CORDIS Project
Funding breakdown and partner intelligence are Premium
Sign in and upgrade to Premium for EU contribution totals, consortium analytics, OpenAlex research context, and AI summaries. · 0 consortium intelligence fields visible of 1
Start free • Cancel anytime • 14-day refund guarantee
This project aims to create efficient algorithms for large-scale machine learning by integrating optimization and statistical advancements. The goal is to reduce the computational resources required for processing large datasets, enhancing the applicability of machine learning in various fields.
This project will develop and integrate the latest optimization and statistical advances into a new generation of resource-efficient algorithms for large-scale machine learning.
State-of-the-art machine learning methods provide impressive results, opening new perspectives for science, technology, and society.
However, they rely on massive computational resources to process huge manually annotated data-sets.
The corresponding costs in terms of energy consumption and human efforts are not sust…
UNIVERSITA DEGLI STUDI DI GENOVA
Partner organizations (coordinator is shown above), with normalized type and CORDIS activity type. Guests see up to 4 partners.
Similar projects, consortium collaboration history, frequent partners, and OpenAlex research context.
Guests see up to 5 topics.
