Objective
Learning to input data into a set of classes, given a set of classification examples, is the main subject to a multidisciplinary field of machine learning. The problem can be formulated as a minimization of a given cost function over possible classification functions. The properties of learning systems crucial for a successful application are: performance, i.e. high accuracy of classification, which depends on how well the used cost function corresponds to the application at hand, scalability, i.e ensuring that memory and time complexity of the learning grows gracefully with data size, and ability to process examples online as they come.
The objectives of this proposal are twofold. First, I intend to develop scalable systems that learn online and use structured (hence more natural) costs. These theoretical advances will facilitate development of learning-based systems for various applications. Second, I intend to apply these new learning methods in computer security (Intrusion Detection Systems) and bioinformatics (DNA splice site detection). To achieve the first goal, I will design new learning algorithms able to optimise structured costs common in non-Bayesian decision- making. I will build on recent methods from the Support Vector Machines learning, which transform the task to a Quadratic Programming (QP) optimisation.
The main idea of the proposed methodology is to exploit algorithms from computational geometry to derive online QP optimisation able to process large-scale data. A key to application of the pro posed algorithms to intrusion detection and splice site detection problems is understanding the problem-specific semantic constraints imposed by these applications. To achieve the second goal, I will incorporate the available semantic models into the learning algorithms, building on a large previous experience of the host institution (FhG-FIRST) in these respective problems.
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.
- natural sciences computer and information sciences artificial intelligence machine learning supervised learning
- natural sciences computer and information sciences computer security malicious software
- natural sciences biological sciences genetics DNA
- natural sciences mathematics pure mathematics geometry
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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.
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.
FP6-2005-MOBILITY-5
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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.
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.
Coordinator
MUNCHEN
Germany
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.