How does the inference latency and memory footprint of lightweight BERT models compare to random forest classi

Abstract

Abstract: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications. More i

Research Question

How does the inference latency and memory footprint of lightweight BERT models compare to random forest classifiers when deployed for real-time Android malware detection on edge devices?

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Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

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Provenance