no code implementations • 29 Jun 2021 • Jingzheng Li, Hailong Sun, Jiyi Li, Zhijun Chen, Renshuai Tao, Yufei Ge
Learning from multiple annotators aims to induce a high-quality classifier from training instances, where each of them is associated with a set of possibly noisy labels provided by multiple annotators under the influence of their varying abilities and own biases.
