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Extreme Learning Machine (ELM), a competitive machine learning technique for single-hidden-layer feedforward neural networks (SLFNNs), has proven to be efficient and effective algorithm for regression and classification problems. However, traditional ELM involves a large number of hidden nodes for complex real world regression and classification problems which increasing the computation burden. In...
Currently, neural networks deliver state of the art performance on multiple machine learning tasks, mainly because of their ability to learn features. However, the architecture of the neural network still requires problem-specific tuning and the long training times and hardware requirements remain an issue. In this work, the Multi-Scale Auto-Tuned Extreme Learning Machine (MSATELM) architecture is...
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