Self-paced regularization in label distribution learning
Label Distribution Learning is a learning paradigm which outputs a representation of how much each label describes the instance. Research into the paradigm involved machine learning algorithms but did not include deep learning as a possible alternative. Deep learning, a sub-discipline of machine lea...
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Format: | Final Year Project (FYP) |
Language: | English |
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2019
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Online Access: | http://hdl.handle.net/10356/76943 |