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In deep neural networks, inputs in each layer are affected by all previous parameters of input layers, so even small changes in input distributions to the network are delivered to internal layers, for leading to differences between source domain and target domain, which is known as covariate shift. Batch Normalization(BN) is designed to address the issue, and makes normalization for each training...
Identifying users' similarity is a very important researching point because its result can be applied to many application systems. In social networks, the user circles are built not only based on their relationships in real-life, but also on common interests. Some existing approaches cannot fully capture users' similarity from the perspective of their common interests, while some other approaches...
As a fundamental problem in data mining, pattern recognition and machine learning, clustering algorithm has been studied for decades, and has been improved in many aspects. However, parameter-free clustering algorithms are still quite weak, which makes their potential generalization to a lot of promising applications rather difficult. A parameter-free clustering algorithm based on density model is...
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