… The experiments show that using expert-… expert-generated data and crowd-generated
data, and (ii) we demonstrate the effectiveness of using expert-generated data on a real crowd…

… In this section we develop a similar algorithm to learn a regression function using annotations
from multiple experts. In the CAD domain as a part of the annotation process a common …

… To measure the uncertainty of the model, we compare the results of multiple learning-fromcrowd
models. For simplicity’s sake, we use two learningfrom-crowd models (A1 and A2) to …

… well for highly biased or noisy crowd labels. Motivated by this limitation … crowd data, we
propose to improve the performance of crowdsourcing learning tasks with some additional expert …

… item to be labeled and the expert to label it at each step in the learning process. In particular…
active learning framework that jointly considers querying the crowd and domain experts for …

… But, if we have found a domain expert among the crowd, can the rest of the annotators
contribute or should we ignore them? To answer this key question, let us assume that we are able …

… gle domain expert can provide the required supervision; for example, ground-truth labels
in … This makes it possible for not just one but many experts (and non-experts) to offer some …

… Our findings show that the majority of investors in this market, the crowd, although … crowd.
Contrary to popular perceptions of crowdfunding platforms as substitutes for traditional expert-…

… We propose a framework called Expert Label Injected Crowd Estimation (ELICE) for … from
the crowd and a few labels form the experts of the field. We assume that experts always provide …

… As an alternative to relying on experts, we investigate the effectiveness of peers as a
source of feedback for improving performance on knowledge-based crowd computing …