Objective
Modern data analysis and optimization rely on our ability to process rapidly evolving dynamic datasets, often involving matrix operations in very high dimensions. Dynamic data structures enable fast information-retrieval on these huge databases by maintain- ing implicit information on the underlying data. As such, understanding the power and limitations of dynamic (matrix) data structures is a fundamental question in theory and practice. Despite decades of research, there are still very basic dynamic problems whose complexity is (exponen- tially) far from understood – Bridging this gap is one of the centerpieces of this proposal.
The second theme of this proposal is advancing the nascent role of dynamic data structures in continuous optimization. For over a century, the traditional focus of optimization research was on minimizing the rate of convergence of local-search methods. The last ∼3 years have witnessed the dramatic potential of dynamic data structures in reducing the cost-per-iteration of (Newton type) optimization algorithms, proclaiming that the bottleneck to accelerating literally thousands of algorithms, is efficient maintenance of dynamic matrix functions. This new framework is only at its early stages, but already led to breakthroughs on decade-old problems in computer science. This proposal will substantially develop this interdisciplinary theory, and identifies the mathematical machinery which would lead to ultra-fast first and second-order convex optimization.
In the non-convex setting, this proposal demonstrates the game-changing potential of dynamic data structures and algebraic sketching techniques in achieving scalable training and inference of deep neural networks, a major challenge of modern AI. Our program is based on a novel connection of Kernel methods and compressed sensing techniques for approximate matrix multiplication.
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.
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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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HORIZON.1.1 - European Research Council (ERC)
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-ERC - HORIZON ERC Grants
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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) ERC-2021-STG
See all projects funded under this callHost institution
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.
91904 JERUSALEM
Israel
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.