FSDR: A Novel Deep Learning-based Feature Selection Algorithm for Pseudo Time-Series Data using Discrete Relaxation

no code implementations • 13 Mar 2024 • Mohammad Rahman, Manzur Murshed, Shyh Wei Teng, Manoranjan Paul

Conventional feature selection algorithms applied to Pseudo Time-Series (PTS) data, which consists of observations arranged in sequential order without adhering to a conventional temporal dimension, often exhibit impractical computational complexities with high dimensional data.

feature selection Time Series

Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection

no code implementations • 1 Jun 2023 • Mst Shapna Akter, Hossain Shahriar, Sheikh Iqbal Ahamed, Kishor Datta Gupta, Muhammad Rahman, Atef Mohamed, Mohammad Rahman, Akond Rahman, Fan Wu

Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems.

Malware Classification Quantum Machine Learning

A New Statistical Framework for Genetic Pleiotropic Analysis of High Dimensional Phenotype Data

no code implementations • 3 Dec 2015 • Panpan Wang, Mohammad Rahman, Li Jin, Momiao Xiong

The widely used genetic pleiotropic analysis of multiple phenotypes are often designed for examining the relationship between common variants and a few phenotypes.

Computational Efficiency