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Malware-DNA: Machine Learning for Malware Analysis that Treats Malware as Mutations in the Software Genome

Malware is one of the most dangerous and costly cyber threats to organizations, the public, and national security, and a crucial factor in modern warfare. The adoption of ML-based solutions against malware threats has been relatively slow despite the …

Malware-DNA: Machine Learning for Malware Analysis that Treats Malwares as Mutations in the Genome of the Software

Malware is one of the most dangerous and costly cyber threats to organizations, the public, and national security, and a crucial factor in modern warfare. The adoption of ML-based solutions against malware threats has been relatively slow despite the …

Sub-topic and Semantic Sub-structure Extraction via SPLIT: Joint Nonnegative Matrix Factorization (NMF) with Automatic Model Selection

Topic modeling is one of the key analytic techniques for organizing and analysis of large text corpora. One approach to topic modeling is the recently introduced SeNMFk, a method based on semantic non-negative matrix factorization (NMF) with …

One-Shot Federated Group Collaborative Filtering

Non-negative matrix factorization (NMF) with missing-value completion is a well-known effective Collaborative Filtering (CF) method used to provide personalized user recommendations. However, traditional CF relies on a privacy-invasive collection of …

Distributed Out-of-Memory SVD on CPU/GPU Architectures

We propose an efficient, distributed, out-of-memory implementation of the truncated singular value decomposition (t-SVD) for heterogeneous (CPU+GPU) high performance computing (HPC) systems. Various implementations of SVD have been proposed, but most …