ERC Consolidator Grant · 2018
Efficient algorithms for sustainable machine learning
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 sustainable. This project builds on the idea that improving efficiency is a key to scale the ambitions and applicability of machine learning. Achieving efficiency requires overcoming the traditional…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.