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In this work, we exploit a novel algorithm for capturing the Lie group manifold structure of the visual impression. By developing the single-layer Lie group model, we show how the representation learning algorithm can be stacked to yield a deep architecture. In addition, we design a Lie group based gradient descent algorithm to solve the learning problem of network weights. We show that our proposed...
Semi-supervised learning is an important research area in machine learning, which is mainly combined with a little labeled training data from reality, studies the data structure and distribution information from the large number of unlabeled data and makes full use of this information to improve the performance of classification algorithms, and researches the symmetry between the labeled and unlabeled...
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