How does the inference efficiency (throughput, latency) of pruned BERT models compare to quantization-optimize

Abstract

Abstract: In this paper, we present a comparative analysis of benign and malicious Android applications, based on static features. In particular, we focus our attention on the permissions requested by an application. We consider both binary classification of malware versus benign, as well as the multiclass problem, where we classify malware samples into their respective families. Our experiments are based on substantial malware datasets and we employ a wide variety of machine learning techniques, including decision trees and random forests, support vector machines, logistic model trees, AdaBoost, and ar

Research Question

How does the inference efficiency (throughput, latency) of pruned BERT models compare to quantization-optimized random forest classifiers for malware detection on resource-constrained Android devices?

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