Objective
Interior point algorithms and a dramatic growth in computing power have revolutionized optimization in
the last two decades. Highly nonlinear problems which were previously thought intractable are now
routinely solved at reasonable scales. Semidefinite programs (i.e. linear programs on the cone of positive
semidefinite matrices) are a perfect example of this trend: reasonably large, highly nonlinear but convex
eigenvalue optimization problems are now solved efficiently by reliable numerical packages. This in turn
means that a wide array of new applications for semidefinite programming have been discovered,
mimicking the early development of linear programming. To cite only a few examples, semidefinite
programs have been used to solve collaborative filtering problems (e.g. make personalized movie
recommendations), approximate the solution of combinatorial programs, optimize the mixing rate of
Markov chains over networks, infer dependence patterns from multivariate time series or produce optimal
kernels in classification problems.
These new applications also come with radically different algorithmic requirements. While interior point
methods solve relatively small problems with a high precision, most recent applications of semidefinite
programming in statistical learning for example form very large-scale problems with comparatively low
precision targets, programs for which current algorithms cannot form even a single iteration. This
proposal seeks to break this limit on problem size by deriving reliable first-order algorithms for solving
large-scale semidefinite programs with a significantly lower cost per iteration, using for example
subsampling techniques to considerably reduce the cost of forming gradients.
Beyond these algorithmic challenges, the proposed research will focus heavily on applications of convex
programming to statistical learning and signal processing theory where optimization and duality results
quantify the statistical performance of coding or variable selection algorithms for example. Finally,
another central goal of this work will be to produce efficient, customized algorithms for some key
problems arising in machine learning and statistics.
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.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering signal processing
- humanities arts modern and contemporary art cinematography
- natural sciences computer and information sciences artificial intelligence machine learning
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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.
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.
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.
ERC-2010-StG_20091028
See other projects for this call
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.
Host institution
75794 PARIS
France
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.