Machine-Learning Based Objective Function Selection for Community Detection

1 code implementation • 25 Mar 2022 • Asa Bornstein, Amir Rubin, Danny Hendler

In this work, we present NECTAR-ML, an extension of the NECTAR algorithm that uses a machine-learning based model for automating the selection of the objective function, trained and evaluated on a dataset of 15, 755 synthetic and 7 real-world networks.

BIG-bench Machine Learning Community Detection

AMSI-Based Detection of Malicious PowerShell Code Using Contextual Embeddings

no code implementations • 23 May 2019 • Amir Rubin, Shay Kels, Danny Hendler

In this work, we conduct the first study of malicious PowerShell code detection using the information made available by AMSI.

Management

Detecting Malicious PowerShell Commands using Deep Neural Networks

no code implementations • 11 Apr 2018 • Danny Hendler, Shay Kels, Amir Rubin

Microsoft's PowerShell is a command-line shell and scripting language that is installed by default on Windows machines.

Node-Centric Detection of Overlapping Communities in Social Networks

1 code implementation • 6 Jul 2016 • Yehonatan Cohen, Danny Hendler, Amir Rubin

We present NECTAR, a community detection algorithm that generalizes Louvain method's local search heuristic for overlapping community structures.

Social and Information Networks Physics and Society