Label-efficient Training Updates for Malware Detection over Time
Label-efficient Training Updates for Malware Detection over Time explores A model-agnostic framework for malware detection that significantly reduces labeling costs by combining active learning and semi-supervised learning techniques to combat evolving threats.. Commercial viability score: 4/10 in Malware Detection.
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