TV
T.J. Viering
4 records found
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Learning curves plot the performance of a machine learning model against the size of the dataset used for training. Curve fitting is a process that attempts to optimize algorithm parameters by minimizing the error in its loss function, thereby achieving the best possible fit to t
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Although there are many promising applications of a learning curve in machine learning, such as model selection, we still know very little about what factors influence their behaviours. The aim is to study the impact of the inherent characteristics of the datasets on the learning
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Yes, convolutional neural networks are domain-invariant, albeit to some limited extent. We explored the performance impact of domain shift for convolutional neural networks. We did this by designing new synthetic tasks, for which the network’s task was to map images to their mean
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Language similarity is very useful for enrichment data in both Natural Lanuguage Processing (NLP) and Automatic Speech Recognition (ASR). A clustering algorithm could provide an efficient means to define language similarity in a data-driven way. This research investigates the rel
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