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Learning and Analysing Massive / Big complex Data

Objective

"LAMBDA aims at transferring game changing technologies to the European industry in critical areas of Machine learning. Based on recent algorithmic breakthroughs, we adapt sophisticated methods to targeted industries, with a twofold goal: First, to help turn cutting edge tools into innovative software products and processes, tailored to real-world issues. Second, based on the available data, to organise open data repositories / benchmarks, or to simulate data with the same statistical properties, when such data is confidential, following ""anonymisation"".

LAMBDA focuses on two distinct application domains: 3D shape analysis and unstructured data mining. They share challenging features such as inherent complexity in modeling the data, high dimensionality which raises the issue of curse of dimensionality, and the need to address such datasets at a massive scale. Moreover, they correspond to the expertise of the participants. LAMBDA is characterised by a unique blend of theoretically rigorous and geometrically inclined methods, thus supporting a strong aspect of interdisciplinarity between Theory of Algorithms and Machine Learning. This shall be supported by advanced software development, ranging from public-domain prototype implementations to licensed software and integrated libraries, where the latter may be based on the highly-optimised platform BIDMach (UC Berkeley).

LAMBDA strengthens existing links within Europe and across the Atlantic, while creating new synergies in the directions of two industrial domains, namely 3D shape search and insurance data. The two clusters are organised around representative companies in the respective domains. The Project is built so as to support knowledge transfer beyond its lifetime. Besides inter-sectoral collaborations, we exploit the international dimension by associating leading USA Universities, so as to bring state-of-the-art methods developed at the global level into the European framework."

Fields of science (EuroSciVoc)

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Keywords

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.

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.

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.

MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-RISE-2016

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Coordinator

ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINON
Net EU contribution

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.

€ 180 000,00
Address
6 CHRISTOU LADA STR
10 561 ATHINA
Greece

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Region
Αττική Aττική Κεντρικός Τομέας Αθηνών
Activity type
Higher or Secondary Education Establishments
Links
Total cost

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.

€ 180 000,00

Participants (2)

Partners (4)

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