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Article
Research of stacked denoising sparse autoencoder
Learning results depend on the representation of data, so how to efficiently represent data has been a research hot spot in machine learning and artificial intelligence. With the deepening of the deep learning...
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Article
Research on denoising sparse autoencoder
Autoencoder can learn the structure of data adaptively and represent data efficiently. These properties make autoencoder not only suit huge volume and variety of data well but also overcome expensive designing...
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Article
A Review on Feature Binding Theory and Its Functions Observed in Perceptual Process
Binding problem, which is also called feature binding, is primarily about integrating distributed information scattered on different cortical areas in a reasonable way. As a key problem in cognitive science an...
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Article
A density-adaptive affinity propagation clustering algorithm based on spectral dimension reduction
As a novel clustering method, affinity propagation (AP) clustering can identify high-quality cluster centers by passing messages between data points. But its ultimate cluster number is affected by a user-defi...