Classifier-Dependent Benefits of Pseudo-Labeling for Semi-Supervised Android Malware Attribution

arXiv:2609.29564 · cs.LG · Submitted 2026-08-26 · Read on arXiv

cs.LG

Submitted: 2026-08-26

Updated: 2026-08-26

Terminology

• Accuracy — 21× in this paper · explained in 1 episode
• Pseudo-labeling — 18× in this paper · explained in 3 episodes
• Semi-supervised Learning — 8× in this paper · explained in 4 episodes
• Random Forest — 7× in this paper
• F1 Score — 6× in this paper · explained in 3 episodes
• Pseudo-labels — 4× in this paper · explained in 2 episodes
• Logistic Regression — 3× in this paper
• Regularization — 3× in this paper · explained in 3 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Semi-Supervised Learning (SSL) — 2× in this paper · explained in 2 episodes
• Active Learning — 1× in this paper · explained in 6 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Multi-Layer Perceptron — 1× in this paper
• Support Vector Machine — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Semi-supervised classification for dynamic Android malware detection

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