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State-of-the-art neural networks are getting deeper and wider. While their performance increases with the increasing number of layers and neurons, it is crucial to design an efficient deep architecture in order to reduce computational and memory costs. Designing an efficient neural network, however, is labor intensive requiring many experiments, and(More)
Building a good generative model for image has long been an important topic in computer vision and machine learning. Restricted Boltzmann machine (RBM) [5] is one of such models that is simple but powerful. However, its restricted form also has placed heavy constraints on the model’s representation power and scalability. Many extensions have been invented(More)
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