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Towards On-line Domain-Independent Big Data Learning: Novel Theories and Applications

Contributors: Hussain, Amir, Cairns, David

Subject Terms: Slow Feature Analysis, Canonical Correlation Analysis, Laplacian eigenmaps, Linear Discriminant Analysis, Invariance, Dimensionality Reduction, Feature Extraction, Domain Independent Learning, Incremental Learning, Concept Drifts, Web services, Big data, Machine learning, Management information systems, Laplacian matrices, Canonical correlation(Statistics)

File Description: application/pdf

Relation: Malik, Zeeshan Khawar, Amir Hussain, and Jonathan Wu. "Novel biologically inspired approaches to extracting online information from temporal data." Cognitive Computation 6.3 (2014): 595-607.; Malik, Zeeshan Khawar, Amir Hussain, and Jonathan Wu. "An online generalized eigenvalue version of Laplacian Eigenmaps for visual big data." Neurocomputing 173 (2016): 127-136.; http://hdl.handle.net/1893/22591; http://dspace.stir.ac.uk/bitstream/1893/22591/1/thesis.pdf

Availability: http://hdl.handle.net/1893/22591
http://dspace.stir.ac.uk/bitstream/1893/22591/1/thesis.pdf

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