Machine learning with crowdsourcing: A brief summary of the past research and future directions
With crowdsourcing systems, labels can be obtained with low cost, which facilitates the
creation of training sets for prediction model learning. However, the labels obtained from …
creation of training sets for prediction model learning. However, the labels obtained from …
[HTML][HTML] A technical survey on statistical modelling and design methods for crowdsourcing quality control
Online crowdsourcing provides a scalable and inexpensive means to collect knowledge (eg
labels) about various types of data items (eg text, audio, video). However, it is also known to …
labels) about various types of data items (eg text, audio, video). However, it is also known to …
Resource-based view of information systems: Sustainable and transient competitive advantage perspectives
The resource-based view (RBV), or resource-based theory, is one of the oldest and most
influential theories in the field of information systems. This paper contends that it is timely to …
influential theories in the field of information systems. This paper contends that it is timely to …
A Bayesian approach for sequence tagging with crowds
E Simpson, I Gurevych - arXiv preprint arXiv:1811.00780, 2018 - arxiv.org
Current methods for sequence tagging, a core task in NLP, are data hungry, which motivates
the use of crowdsourcing as a cheap way to obtain labelled data. However, annotators are …
the use of crowdsourcing as a cheap way to obtain labelled data. However, annotators are …
Active multilabel crowd consensus
Crowdsourcing is an economic and efficient strategy aimed at collecting annotations of data
through an online platform. Crowd workers with different expertise are paid for their service …
through an online platform. Crowd workers with different expertise are paid for their service …
Human-in-the-loop machine learning with applications for population health
Though technical advance of artificial intelligence and machine learning has enabled many
promising intelligent systems, many computing tasks are still not able to be fully …
promising intelligent systems, many computing tasks are still not able to be fully …
Multi-label answer aggregation based on joint matrix factorization
Crowdsourcing is a useful and economic approach to data annotation. To obtain annotation
of high quality, various aggregation approaches have been developed, which take into …
of high quality, various aggregation approaches have been developed, which take into …
Multi-label crowd consensus via joint matrix factorization
Crowdsourcing is a useful and economic approach to annotate data. Various computational
solutions have been developed to pursue a consensus of high quality. However, available …
solutions have been developed to pursue a consensus of high quality. However, available …
Efficient and adaptive incentive selection for crowdsourcing contests
The success of crowdsourcing projects relies critically on motivating a crowd to contribute.
One particularly effective method for incentivising participants to perform tasks is to run …
One particularly effective method for incentivising participants to perform tasks is to run …
Top feasible arm identification
J Katz-Samuels, C Scott - The 22nd International Conference …, 2019 - proceedings.mlr.press
We propose a new variant of the top arm identification problem,\emph {top feasible arm
identification}, where there are $ K $ arms associated with $ D $-dimensional distributions …
identification}, where there are $ K $ arms associated with $ D $-dimensional distributions …