9 citations · 9 across the 2 of their papers we have counts for
4 papers
M-ar-K-Fast Independent Component Analysis
Luca Parisi
This study presents the m-arcsinh Kernel ('m-ar-K') Fast Independent Component Analysis ('FastICA') method ('m-ar-K-FastICA') for feature extraction. The kernel trick has enabled d…
hyper-sinh: An Accurate and Reliable Function from Shallow to Deep Learning in TensorFlow and Keras
Luca Parisi, Renfei Ma, Narrendar RaviChandran +1
This paper presents the 'hyper-sinh', a variation of the m-arcsinh activation function suitable for Deep Learning (DL)-based algorithms for supervised learning, such as Convolution…
QReLU and m-QReLU: Two novel quantum activation functions to aid medical diagnostics
L. Parisi, D. Neagu, R. Ma +1
The ReLU activation function (AF) has been extensively applied in deep neural networks, in particular Convolutional Neural Networks (CNN), for image classification despite its unre…
m-arcsinh: An Efficient and Reliable Function for SVM and MLP in scikit-learn
Luca Parisi
This paper describes the 'm-arcsinh', a modified ('m-') version of the inverse hyperbolic sine function ('arcsinh'). Kernel and activation functions enable Machine Learning (ML)-ba…