mlsanityData to 7 Oct 2026

NSML: A Machine Learning Platform That Enables You to Focus on Your Models

arXiv 1712.05902 ↗First posted 16 Dec 2017cs.LG cs.DCcited by 34

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Abstract (arXiv)

Machine learning libraries such as TensorFlow and PyTorch simplify model implementation. However, researchers are still required to perform a non-trivial amount of manual tasks such as GPU allocation, training status tracking, and comparison of models with different hyperparameter settings. We propose a system to handle these tasks and help researchers focus on models. We present the requirements of the system based on a collection of discussions from an online study group comprising 25k members. These include automatic GPU allocation, learning status visualization, handling model parameter snapshots as well as hyperparameter modification during learning, and comparison of performance metrics between models via a leaderboard. We describe the system architecture that fulfills these requirements and present a proof-of-concept implementation, NAVER Smart Machine Learning (NSML). We test the system and confirm substantial efficiency improvements for model development.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Dec 2017.

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Citing papers per year: 2021: 12; 2022: 10; 2023: 5; 2024: 5; 2025: 1; 2026: 1.

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