Mohammad Amin Omidi

Reducing the Computational Complexity of Learning with Random Convolutional Features

In the last decade, there has been a surge of research interest in feature extraction using random sampling. These techniques are fast and scalable and, at the same time, have practical favorability in low-sample size and high-dimensional training data. Convolutional Kitchen Sinks-based methods are…