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Content archived on 2024-06-18

Sparse Structured Methods for Machine Learning

Objective

Machine learning is now a core part of many research domains, where the abundance of data has forced researchers to rely on automated information processing. In practice, today, machine learning techniques are applied in two stages: practitioners first build a large set of features; then, off-the-shelf algorithms are used to solve the appropriate prediction tasks, such as classification or regression. While this has led to significant advances in many domains, I believe that the potential of machine learning is far from being fulfilled. The tenet of this proposal is that to achieve the expected breakthroughs, this two-stage paradigm should be replaced by an integrated process where the specific structure of a problem is taken into account explicitly in the learning process. This will allow the consideration of massive numbers of features, in both numerically efficient and theoretically well-understood ways. I plan to attack this problem through the tools of regularization by sparsity-inducing norms. The scientific objective is thus to marry structure with sparsity: this is particularly challenging because structure may occur in various ways (discrete, continuous or mixed) and my targeted applications in computer vision and audio processing lead to large-scale convex optimization problems. My research program is expected to have a high impact on statistical machine learning research, notably by providing new solutions to the open problem of non-linear variable selection. Moreover, my general methodology will be directly applied to domains where the natural structure of data has been recognized as crucial but is still underused by learning techniques, namely computer vision (object recognition, image denoising) and audio processing (speech separation, music recognition).

Fields of science (EuroSciVoc)

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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.

Call for proposal

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

ERC-2009-StG
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Funding Scheme

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ERC-SG - ERC Starting Grant

Host institution

INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
EU contribution
€ 1 468 248,00
Address
DOMAINE DE VOLUCEAU ROCQUENCOURT
78153 Le Chesnay Cedex
France

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Activity type
Research Organisations
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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.

No data

Beneficiaries (1)

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