Description

Machine learning models convert raw data in the form of video, images, audio,

text, etc. into feature representations that are convenient for computational process-

ing. Deep neural networks have proven to be

Machine learning models convert raw data in the form of video, images, audio,

text, etc. into feature representations that are convenient for computational process-

ing. Deep neural networks have proven to be very efficient feature extractors for a

variety of machine learning tasks. Generative models based on deep neural networks

introduce constraints on the feature space to learn transferable and disentangled rep-

resentations. Transferable feature representations help in training machine learning

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    Date Created
    • 2018
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  • Text
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    • Masters Thesis Computer Science 2018

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