Designing active learning algorithms for a crowd-sourced database poses many practical challenges: such algorithms need to be generic, scalable, and easy to use ...

This paper proposes algorithms for integrating machine learning into crowd-sourced databases in order to combine the accuracy of human labeling with the speed ...

This paper proposes algorithms for integrating machine learning into crowd-sourced databases in order to combine the accuracy of human labeling with the ...

Jan 13, 2024 · This paper proposes algorithms for integrating machine learning into crowd-sourced databases in order to combine the accuracy of human labeling ...

Sep 9, 2016 · This paper proposes algorithms for integrating machine learning into crowd-sourced databases in order to combine the accuracy of human labeling ...

Sep 17, 2012 · Based on this observation, we present two new active learning algorithms to combine humans and algorithms together in a crowd-sourced database.

Apr 17, 2018 · 论文Scaling Up Crowd-Sourcing to Very Large Datasets A Case for Active Learning提出两种AL算法。 首先找到分类器θ对未标注数据的不确定程度。

Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning ... Download the Active Learning and Crowdsourced Datasets (Sentiment Analysis ...

Scaling up crowd-sourcing to very large datasets: a case for active learning. B Mozafari, P Sarkar, M Franklin, M Jordan, S Madden. Proceedings of the VLDB ...

Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning · Computer Science. Proc. VLDB Endow. · 2014.