A Light-weight, Effective and Efficient Model for Label Aggregation in Crowdsourcing

19 November 2022

Papers citing "A Light-weight, Effective and Efficient Model for Label Aggregation in Crowdsourcing"

8 / 8 papers shown

Title
Streaming Bayesian Inference for Crowdsourced Classification Edoardo Manino Long Tran-Thanh N. Jennings 31 5 0 13 Nov 2019
An Unsupervised Bayesian Neural Network for Truth Discovery in Social Networks Jielong Yang Wee Peng Tay BDL 43 8 0 25 Jun 2019
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers Yao Ma Alexander Olshevsky Venkatesh Saligrama Csaba Szepesvári 34 25 0 25 Apr 2019
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations Yuan Li Benjamin I. P. Rubinstein Trevor Cohn 38 31 0 24 Feb 2019
A Technical Survey on Statistical Modelling and Design Methods for Crowdsourcing Quality Control Yuan Jin Mark J. Carman Ye Zhu Yong Xiang 15 35 0 05 Dec 2018
Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing Hongwei Li Bin Yu FedML 50 89 0 15 Nov 2014
Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing Yuchen Zhang Xi Chen Dengyong Zhou Michael I. Jordan FedML 55 386 0 15 Jun 2014
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems David R Karger Sewoong Oh Devavrat Shah 70 380 0 17 Oct 2011