Objective
The modelling of real-life nonlinear processes is commonly done via local linearization, i.e. by fitting linear models to small
ranges of the process. Linearization is, however, quite limited in range and model properties. A foundational step is currently being made by moving from linear to multi-linear or polynomial models to capture more general features of a nonlinear process over larger ranges. A second important development is Big Data: nowadays we often encounter high-dimensional datasets with multiple `independent’ modes of variation. This increases the numbers of equations and variables and the degrees of the polynomials in the multi-linear models that are required. Big Data research is a key priority in the EU Horizon 2020 Work Programme.
This proposal joins both the cutting edge multi-linear and Big Data developments and as a next step aims to develop new robust and efficient numerical methods to solve large polynomial systems. Polynomial equations arise naturally in a large number of diverse fields such as signal processing, robotics, coding theory, optimization, bioinformatics, computer vision, game theory, statistics, machine learning, and systems and control theory. In many applications the coefficients of the polynomials are noisy (i.e. computed from measured data). Currently, solving polynomial equations is commonly done via ‘symbolic algebra’ tools, but these are not suitable for equations with noisy coefficients. However, the rediscovered work of Sylvester and Macaulay puts the problem in a linear algebra setting and well-known numerical linear algebra tools can be used. This project will go beyond this and uses new highly efficient multi-linear algebra tools in the field of tensor decompositions. The latter are higher-order generalizations of the matrix singular valued decomposition.
The project combines polynomial algebra, numerical linear algebra, and multi-linear algebra, and will have large impact on a large number of applications.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences mathematics pure mathematics algebra linear algebra
- natural sciences computer and information sciences data science big data
- natural sciences computer and information sciences artificial intelligence computer vision
- natural sciences mathematics applied mathematics game theory
- natural sciences mathematics applied mathematics numerical analysis
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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)
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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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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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) H2020-MSCA-IF-2016
See all projects funded under this callCoordinator
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.
3000 LEUVEN
Belgium
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.