Learning from Crowds by Modeling Common Confusions

Learning from Crowds by Modeling Common Confusions

24 December 2020

Papers citing "Learning from Crowds by Modeling Common Confusions"

11 / 11 papers shown

Title
Mixture of Experts based Multi-task Supervise Learning from Crowds Tao Han Huaixuan Shi Xinyi Ding Xiao Ma Huamao Gu Yili Fang 52 0 0 18 Jul 2024
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds Peng Cao Yilun Xu Yuqing Kong Yizhou Wang 20 55 0 31 May 2019
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion Ryutaro Tanno A. Saeedi S. Sankaranarayanan Daniel C. Alexander N. Silberman NoLa 52 230 0 10 Feb 2019
Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model Hideaki Imamura Issei Sato Masashi Sugiyama 33 25 0 13 Feb 2018
Deep learning from crowds Filipe Rodrigues Francisco Câmara Pereira FedML NoLa 40 257 0 06 Sep 2017
Who Said What: Modeling Individual Labelers Improves Classification M. Guan Varun Gulshan Andrew M. Dai Geoffrey E. Hinton NoLa 33 226 0 26 Mar 2017
A Permutation-based Model for Crowd Labeling: Optimal Estimation and Robustness Nihar B. Shah Sivaraman Balakrishnan Martin J. Wainwright FedML 36 44 0 30 Jun 2016
Achieving Budget-optimality with Adaptive Schemes in Crowdsourcing A. Khetan Sewoong Oh 30 74 0 10 Feb 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 328 43,154 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 854 149,474 0 22 Dec 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