A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Abstract: With the advent of ubiquitous sensing and networking, future social networks turn into cyber-physical interactions, which are attached with associated social attributes. Therefore, social ...

Most of the models are completed in a single file and implemented in a simple way. The machine learning part of the code does not use any external libraries, except for the loading part of the ONNX ...

This repository contains code for our SPAA paper "Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable" (SPAA'18). It includes implementations of the following parallel graph ...

You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...

Mathematicians recently gathered for a workshop in Canada a to thrash out ideas inspired by a breakthrough a pair of researchers made in 2023 on a conjecture by Paul Erdős. The pair’s success at ...

Abstract: Mining cohesive subgraphs from a network is a fundamental problem in network analysis. Most existing cohesive subgraph models are mainly tailored to unsigned networks. In this paper, we ...