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The bounds on the rate of uniform convergence of learning processes play an important role in the Statistical Learning Theory. They provide theoretical bases for the application of support vector machine and reflect the generalization ability of the learning machines. This paper mainly deals with the bounds on the rate of uniform convergence of learning processes when samples are corrupted by equality-expect...
Quasi-probability is a kind of typical non-additive measure, which has similar structure with probability, and is widely applied in some practical application. In this paper, some new properties of quasi-probability are presented. The concepts of distribution function, expected value and variance on quasi-probability space are put forward and some related properties are given and proven
Based on statistical learning theory on probability space and good properties of quasi-probability, some important inequalities are proven on quasi-probability space in this paper. Furthermore, some new concepts of learning theory are given and the key theorem of statistical learning theory is given and proven when samples are corrupted by equality-expect noise on quasi-probability space
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