Kernel-based neural network (KNN) is proposed as a neuron that is applicable in online learning with adaptive parameters. This neuron with adaptive kernel parameter can classify data accurately instead of using a multilayer ...

Online kernel methods suffer from computational and memory complexity in large-scale problems. Due to these drawbacks, budget online kernel learning and kernel approximation (low-dimensional feature map approximation) methods are widely used...

In this paper, we propose a special fusion

method for combining ensembles of base classifiers

utilizing new neural networks in order to improve

overall efficiency of classification. While ensembles ...

This article concerns an almost sure representation with rate for a new estimator of a survival function in the setting of length-biased and right-censored data. This representation will be the key to obtain the asymptotic ...