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Content archived on 2024-06-18

Sublinear Optimization for Machine Learning

Objective

The explosion of data with the expansion of the World Wide Web, social networking and e-commerce is a ripe opportunity for smart data analysis and machine learning on a scale never before encountered. In many applications, making even a few passes over the data is prohibitive. Our research goal is to develop sublinear time optimization algorithms for data analysis and machine learning, i.e. algorithms that do not observe all the data even once, and yet return a provably correct solution with high probability.

Previous research of the PI, conducted mainly at Princeton University and IBM Research, has produced promising preliminary results. This proposal aims to expand this line of research at the host institution.

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.

Call for proposal

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FP7-PEOPLE-2010-RG
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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.

MC-IRG - International Re-integration Grants (IRG)

Coordinator

TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
EU contribution
€ 100 000,00
Address
SENATE BUILDING TECHNION CITY
32000 Haifa
Israel

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Activity type
Higher or Secondary Education Establishments
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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.

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