Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

The application of several high-throughput genomic and proteomic technologies to address questions in cancer diagnosis, prognosis and prediction generate high-dimensional data sets. The multimodality ...

Getting AI governance right is one of the most consequential challenges of our time, calling for mutual learning based on the lessons and good practices emerging from the different jurisdictions ...

Overview This repository provides a reusable Gaussian Mixture Model implementation trained with Expectation-Maximization using pure numpy. It supports full, diagonal, and spherical covariances, ...

Abstract: The reception of data frames over long-distance, low-power communication networks is impacted by channel interference, often leading to partial data loss. This issue is particularly ...

This repository contains comprehensive implementations of algorithms from the classic textbook "Fundamentals of Computer Algorithms" (Second Edition) by Ellis Horowitz, Sartaj Sahni, and Sanguthevar ...