Objective
The advances in technology over the last decade and the massive amount of data passing through the internet has intrigued and challenged computer scientists, as the old models of computation used before this era are now
less relevant or too slow. New computational models have been suggested to tackle these technological advances. In the most basic sense, these modern models allow one
to scan the input only once, possible with small auxiliary memory. Nevertheless, modern techniques have also been introduced such as sparse recovery which has proven
to be a very useful tool for dealing with modern challenges, and the very popular notion of conditional lower bounds which has provided evidence of hardness for various algorithmic tasks based on very popular conjectures.
Pattern matching plays a crucial role in many computing applications that can be seen in day to day life. However, its research community has only recently started gaining insight on what can be done in modern models, and is lagging behind in this respect. In particular, there are no algorithms for pattern matching problems that have utilized ideas from sparse recovery, and only recently has there been progress in proving conditional lower bounds for string problems. Furthermore, conditional lower bounds suffer from the lack of hardness conjectures which address time/space tradeoffs.
This proposal will close this gap for many important pattern matching problems within the new models of computation, and will be the first to utilize modern algorithmic techniques, such as sparse
recovery, and adapting them into the pattern matching world. Furthermore, this proposal will focus on
developing a theory for proving conditional time/space lower bounds, based on new hardness conjectures. This will greatly influence not only the pattern matching sub-field, but the entire algorithmic field at large.
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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H2020-EU.1.1. - EXCELLENT SCIENCE - 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.
ERC-COG - Consolidator Grant
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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-2015-CoG
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.
52900 Ramat Gan
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.