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Efficient algorithms for sustainable machine learning

Project description

New algorithms to make machine learning sustainable

Machine learning is they key component behind the recent successes of intelligent systems and data analytics engines. Machine learning algorithms trained on data can perform impressive tasks, but often at the expense of massive computational resources. Lessening these requirements is the goal of the EU-funded SLING project. SLING will develop a new generation of resource-efficient algorithms for large-scale machine learning solutions, readily applicable to real-world scenarios. The solutions developed in the project will make machine learning more accessible and sustainable, greatly boosting the prospects of developing truly scalable intelligent systems.

Call for proposal

ERC-2018-COG
See other projects for this call

Host institution

UNIVERSITA DEGLI STUDI DI GENOVA
Address
Via Balbi 5
16126 Genova
Italy
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 977 500

Beneficiaries (1)

UNIVERSITA DEGLI STUDI DI GENOVA
Italy
EU contribution
€ 1 977 500
Address
Via Balbi 5
16126 Genova
Activity type
Higher or Secondary Education Establishments