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We introduce a new method for classification called the influence machine. The influence machine assigns influence powers to the instances in the training sample so that they can apply their influence to other instances through the connections between the instances specified by a connection matrix. A new instance is classified to be positive if the overall influence it receives is positive and vice...
Transfer learning is a new learning paradigm, in which, besides the training data for the targeted learning task, data that are related to the task (often under a different distribution) are also employed to help train a better learner. For example, out-dated data can be used as such related data. In this paper, we propose a new transfer learning framework for training neural network (NN) ensembles...
Traffic classifications based on Statistics methods and Machine Learning techniques have attracted a great deal of interest. One challenging issue is that most of supervised algorithms need traffic application information and training data sets to generate classification model offline, which is infeasible to cope with the fast growing number of new applications and online traffic classifications....
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