Li'ang Yin

Aggregating Crowd Wisdom with Side Information via a Clustering-based Label-aware Autoencoder

Aggregating crowd wisdom infers true labels for objects, from multiple noisy labels provided by various sources. Besides labels from sources, side information such as object features is also introduced to achieve higher inference accuracy. Usually, the learning-from-crowds framework is adopted. Howe…