dc.contributor.authorBai, Zuo
dc.date.accessioned2015-12-01T08:22:50Z
dc.date.accessioned2017-07-23T08:36:12Z
dc.date.available2015-12-01T08:22:50Z
dc.date.available2017-07-23T08:36:12Z
dc.date.copyright2015en_US
dc.date.issued2015
dc.identifier.citationBai, Z. (2015). Extreme learning machine with sparse connections. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/65656
dc.description.abstractThe thesis is in the field of machine learning, and specifically studies the recent emerging algorithm, Extreme Learning Machine (ELM). Unlike previous ELM implementations, in which hidden nodes are in full connection with the input ones, we present the ELM with sparse connections. In one way, it reduces the storage space and testing time, while providing better scalability for large-scale applications. In the other way, the sparse connections make it especially suitable and efficient for locally correlated applications, such as image processing, speech recognition, etc.en_US
dc.format.extent143 pen_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognitionen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleExtreme learning machine with sparse connectionsen_US
dc.typeThesis
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.supervisorWang Dan Wei
dc.contributor.supervisorHuang Guangbinen_US
dc.description.degreeDOCTOR OF PHILOSOPHY (EEE)en_US


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