This paper presents a novel method to solve the problem that knowledge has plenty of attributes in learning

The purpose of this talk is to analyze new hybrid proximal point algorithms and solve the constrained minimization problem involving a convex functional in a uni- formly convex

This kind of algorithm has also been a powerful tool for solving many other optimization problems, including symmetric cone complementarity problems [15, 16, 20–22], symmetric

For the data sets used in this thesis we find that F-score performs well when the number of features is large, and for small data the two methods using the gradient of the

We present a new method, called ACC (i.e. Association based Classification using Chi-square independence test), to solve the problems of classification.. ACC finds frequent and

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(2) We emphasized that our method uses compressed video data to train and detect human behavior, while the proposed method of [19] Alireza Fathi and Greg Mori can only

To solve this problem, this study proposed a novel neural network model, Ecological Succession Neural Network (ESNN), which is inspired by the concept of ecological succession

Therefore, a new method, which is based on data mining technique, is proposed to classify driving behavior in multiclass user traffic flow.. In this study, driving behaviors