The accurate and timely monitoring of regional urban extent is helpful for analyzing urban
sprawl and studying environmental issues related to urbanization. This paper proposes a …

Abstract Support Vector Machines (SVMs) are vulnerable to integrity attacks, where
malicious attackers distort the training data in order to compromise the decision boundary of …

As a novel representation method, two dimensional (2D) segmentation is gaining ground as
an effective condition monitoring method due to its high-level information descriptional …

We derive the calculation of two critical numbers predicting the behavior of perceptron
networks. First, we derive the calculation of what we call the lossless memory (LM) …

The classification of complex data usually requires the composition of processing steps.
Here, a major challenge is the selection of optimal algorithms for preprocessing and …

Memorization is worst-case generalization. Based on MacKay's information theoretic model
of supervised machine learning, this article discusses how to practically estimate the …

For many real-life problems obtaining representative examples from a given class is
relatively easy, while for the remaining ones are difficult, or even impossible. However, we …

Data processing often transforms a complex signal using a set of different preprocessing
algorithms to a single value as the outcome of a final decision function. Still, it is challenging …

Online support vector data description (SVDD) performs excellently when dealing with
novelty detection problems. This method only uses the support vectors (SVs) as an initial …

Abstract MACHINE learning models are increasingly being used for automated decision
making in a wide range of domains such as security, finance, and communications. Machine …