[2211.12620] Promises and Pitfalls of Threshold|based Auto|labeling
[2211.12620] Promises and Pitfalls of Threshold-based Auto-labeling
This is the first work to analyze TBAL systems and derive sample complexity bounds on the amount of human-labeled validation data required for guaranteeing the ...
Promises and Pitfalls of Threshold-based Auto-labeling - arXiv
arXiv:2211.12620v2 [cs.LG] 22 Feb 2024. Promises and Pitfalls of Threshold-based Auto-labeling. Report issue for preceding element. Harit Vishwakarma
Promises and Pitfalls of Threshold-based Auto-labeling - NIPS papers
Threshold-based auto-labeling (TBAL), where validation data obtained from humans is used to find a confidence threshold above which the data is machine-labeled, ...
Promises and Pitfalls of Threshold-based Auto-labeling
Creating large-scale high-quality labeled datasets is a major bottleneck in supervised machine learn- ing workflows. Threshold-based auto-labeling. (TBAL), ...
Good Data from Bad Models : Foundations of Threshold-based Auto ...
Together, these insights describe the promise and pitfalls of using such systems. We validate our theoretical guarantees with simulations and study the ...
Heguang Lin - Google Scholar
Promises and pitfalls of threshold-based auto-labeling. H Vishwakarma, H Lin, F Sala, R Korlakai Vinayak. Advances in Neural Information Processing Systems 36, ...
Promises and Pitfalls of Threshold-based Auto-labeling. NeurIPS 2023; 2022 ... Good Data from Bad Models : Foundations of Threshold-based Auto-labeling. CoRR abs/ ...
Heguang Lin - Google Scholar
Promises and pitfalls of threshold-based auto-labeling. H Vishwakarma, H Lin ... arXiv preprint arXiv:2211.12620, 2022. 1, 2022. Human-in-the-Loop Out-of ...
Promises and pitfalls of threshold-based auto-labeling. H Vishwakarma, H Lin ... H Vishwakarma, H Lin, F Sala, RK Vinayak. arXiv preprint arXiv:2211.12620, 2022.
Search | arXiv e-print repository - CoNexa Pro
arXiv:2211.12620 [pdf, other]. cs.LG cs.AI stat.ML. Promises and Pitfalls of Threshold-based Auto-labeling. Authors: Harit Vishwakarma, Heguang Lin, Frederic ...
harit7/TBAL: Promises and Pitfalls of Threshold-based Auto-labeling ...
This repository provides code for the experiments in our paper, Promises and Pitfalls of Threshold-based Auto-labeling, NeurIPS 2023 (Spotlight)