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This paper proposes the use of Stacked Denoising Autoencoder to predict the direction of movement of stock indexes based on the historical and volume data of the underlying stocks. The Stacked Denoising Autoencoder is a deep learning method widely used in the field of computer vision which is capable of learning a compact feature representation of the data for stock index prediction. The Hybrid Gravitational...
Traditional multi-class image classification needs a large number of training samples for building a classifier model. However, it is very time-consuming and costly to obtain labels for a large number of training samples from human experts. Active learning is a feasible solution. This paper proposes a maximum classification optimization method (MCO) for actively selecting unlabeled images to acquire...
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