mlsanityData to 14 Oct 2026

Benchmarking Machine Learning: How Fast Can Your Algorithms Go?

arXiv 2101.03219 ↗First posted 8 Jan 2021cs.LGcited by 3

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Abstract (arXiv)

This paper is focused on evaluating the effect of some different techniques in machine learning speed-up, including vector caches, parallel execution, and so on. The following content will include some review of the previous approaches and our own experimental results.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 0 of its 50 references that are in the map. First posted on arXiv 8 Jan 2021.

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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1.

3 papers.