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DC Field | Value | Language |
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dc.contributor.author | Guan, SU | - |
dc.contributor.author | Li, P | - |
dc.coverage.spatial | 32 | en |
dc.date.accessioned | 2008-03-10T13:29:09Z | - |
dc.date.available | 2008-03-10T13:29:09Z | - |
dc.date.issued | 2002 | - |
dc.identifier.citation | Journal of Intelligent Systems. 12 (3) 201-226 | en |
dc.identifier.issn | 0334-1860 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/1823 | - |
dc.description.abstract | In this paper, we suggest a new task decomposition method – hierarchical incremental class learning (HICL). In this approach, a -class problem is divided into sub-problems. The sub-problems are learnt sequentially in a hierarchical structure with sub-networks. Each sub-network takes the output from the sub-network immediately below it as well as the original input as its input. The output from each sub-network contains one more class than the sub-network immediately below it, and this output is fed into the sub-network above it. It not only reduces harmful interference among hidden layers, but also facilitates information transfer between classes during training. The later sub-networks can obtain learnt information from the earlier sub-networks. We also proposed two ordering algorithms – MSEF and MSEF-FLD to determine the hierarchical relationship between the sub-networks. The proposed HICL approach shows smaller regression error and classification error than the class decomposition and retraining approaches. | en |
dc.format.extent | 175021 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | Freund & Pettman | en |
dc.relation.ispartof | 12;3 | - |
dc.subject | Neural network | en |
dc.subject | Task decomposition | en |
dc.subject | Incremental learning | en |
dc.subject | Ordering | en |
dc.title | A hierarchical incremental learning approach to task decomposition | en |
dc.type | Research Paper | en |
Appears in Collections: | Electronic and Computer Engineering Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
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A Hierarchical Incremental Learning Approach to Task Decomposition.txt | 285 B | Text | View/Open |
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