| EPSRC Reference: |
GR/M99033/01 |
| Title: |
KERNAL METHODS FOR SEQUENCES AND SENTENCES |
| Principal Investigator: |
Watkins, Professor CJC |
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| Department: |
Computer Science |
| Organisation: |
Royal Holloway, Univ of London |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 October 1999 |
Ends: |
30 September 2002 |
Value (£): |
50,590
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Summary on Grant Application Form |
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The programme is to invent, develop, and evaluate kernel methods of applying linear statistics to types of data to which linear statistics has not previously been naturally applied, such as biological sequence, speech data, and grammatical sentences.A kernel is a symmetric function of two variables, which can be represented as a scalar product: a kernel, therefore, implicitly defines a mapping from its arguments to a Euclidean feature space .Given data such as DNA sequences, recordings of speech, or sentences, defining a kernel function enables a feature vector for each data item to be represented indirectly. The advantage is that very large feature vectors may be represented economically in this way, and linear statistical computations can still be performed.The research will consist of dveloping kernels, trying them out on real and synthetic data, and after anlysing the representations they produce, attempting to improve the kernels. Two other areas of work are to use combinatoric analysis of matching operations to characterise the geometric properties of the feature space mappings, and to develop computational methods to cope with near-orthogonal feature-vectors.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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