Objective
With the rapid evolution of Artificial Intelligence, distributed machine learning methods such as Federated Learning (FL) are becoming ubiquitous in present-day technology. In FL, devices train neural network models while data stays local. A central entity then aggregates the model updates into a global model. Split learning (SL) has been recently proposed as a way to enable resource-constrained devices to participate in this learning framework. In a nutshell, SL splits the model into parts, and allows clients (devices) to offload the largest part as a processing task to a computationally powerful helper (edge server, cloud, or other devices). Essentially, SL is a paradigm shift offering a more flexible version of FL that alleviates the load at the devices by better utilizing other available resources in the network. However, this method comes with optimization challenges since networking decisions need to be made in order to orchestrate the SL operations and overcome any communication overhead. Despite the increasing attention towards SL, current algorithms focus on minimizing the training time and improving on energy efficiency, without however bearing any performance guarantees. In order to make SL efficient, OPALS will fill this crucial gap by providing algorithms with provable guarantees. In particular, OPALS focuses on 3 main research axes. First, it studies the well-established problem of minimizing the training time, in search of the first algorithm with guarantees. Second, it seeks ways of leveraging SL to reduce the carbon footprint of distributed learning. Third, it investigates how SL could be employed in a decentralized setting in view of the increasing importance of swarm intelligence. OPALS will employ mathematical modelling and cutting-edge optimization methods to achieve these goals. As a result, OPALS will pave the way to better resource utilization, and thus, efficient SL exploitable for technological innovation.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
28050 MADRID
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.