Feature selection for various applications has been carried out for many years in many different research areas. However, there is a trade-off between finding feature subsets with minimum length and increasing the classification accuracy. In this paper, a filter-wrapper feature selection approach based on fuzzy-rough gain ratio is proposed to tackle this problem. As a search strategy, a modifie...

Data annotation using visual inspection (supervision) of each training sample can be laborious. Interactive solutions alleviate this by helping experts propagate labels from a few supervised samples to unlabeled ones based solely on the analysis their feature space projection (with no further supervision). We present semi-automatic data approach suitable and semi-supervised label estimation. va...

<p style='text-indent:20px;'>In this paper we combine an approach based on Runge-Kutta Nets considered in [<i>Benning et al., J. Comput. Dynamics, 9, 2019</i>] and a technique augmenting the input space [<i>Dupont NeurIPS</i>, 2019] to obtain network architectures which show better numerical performance for deep neural networks point image classification problems. ...

We present a new algorithm to train robust malware detector. Malware is prolific problem and detectors are front-line defense. Modern rely on machine learning algorithms. Now, the adversarial objective devise alterations code decrease chance of being detected whilst preserving functionality realism malware. Adversarial effective in improving robustness but generating functional realistic sample...