29 search results - page 1 / 6 » Learning to rank from a noisy crowd |
SIGIR
2011
ACM
12 years 7 months ago
2011
ACM
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
JMLR
2010
12 years 11 months ago
2010
For many supervised learning tasks it may be infeasible (or very expensive) to obtain objective and reliable labels. Instead, we can collect subjective (possibly noisy) labels fro...
WWW
2008
ACM
14 years 5 months ago
2008
ACM
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
KDD
2012
ACM
11 years 7 months ago
2012
ACM
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
CVPR
2009
IEEE
13 years 8 months ago
2009
IEEE
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...