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Found 2 papers, 1 papers with code
Deep learning at the shallow end: Malware classification for non-domain experts
Current malware detection and classification approaches generally rely on time consuming and knowledge intensive processes to extract patterns (signatures) and behaviors from malware, which are then used for identification.
Ranked #1 on
Malware Classification
on Microsoft Malware Classification Challenge
(F1 score (5-fold) metric)
Topic Stability over Noisy Sources
Topic modelling techniques such as LDA have recently been applied to speech transcripts and OCR output.
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