Jun 15, 2014 · Abstract:Crowdsourcing is a popular paradigm for effectively collecting labels at low cost. The Dawid-Skene estimator has been widely used ...
This work not only provides an optimal algorithm for crowdsourcing but provides new general insight into the method of moments. Empirical studies show that when ...
As a remedy, most crowdsourcing services resort to labeling redundancy, collecting multiple labels from different workers for each item. Such a strategy raises ...
[PDF] Spectral Methods Meet EM: A Provably Optimal Algorithm for ...
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Our method for initializing the EM algorithm in crowdsourcing is inspired by recent work using spectral methods to estimate latent variable models [3, 1, 4 ...
Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing · Figures and Tables · Topics · Ask This Paper · 358 Citations · 33 References · Related ...
Jan 1, 2016 · In this paper, we propose a two-stage efficient algorithm for multi-class crowd labeling problems. The first stage uses the spectral method to ...
Sep 28, 2018 · Crowdsourcing is a popular paradigm for effectively collecting labels at low cost. The Dawid-Skene estimator has been widely used for ...
Spectral Methods: Latent parameters (e.g. y and µ) can be recovered from the first three moments of data. Hidden Markov Model (Hsu, Kakade and Zhang, 2012).
In this paper, we propose a two-stage effi- cient algorithm for multi-class crowd labeling problems. The first stage uses the spectral method to obtain an ...
Codes and data for the paper 'Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing' (http://jmlr.org/papers/volume17/14-511/14-511.pdf).