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    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...

    Lingheng Meng, Shifei Ding, Nan Zhang, Jian Zhang in Neural Computing and Applications (2018)

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    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...

    Lingheng Meng, Shifei Ding, Yu Xue in International Journal of Machine Learning … (2017)

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    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...

    Shifei Ding, Lingheng Meng, Youzhen Han, Yu Xue in Cognitive Computation (2017)

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    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...

    Hongjie Jia, Shifei Ding, Lingheng Meng, Shuyan Fan in Neural Computing and Applications (2014)