MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering

1 code implementation • ICLR 2021 • Tsung Wei Tsai, Chongxuan Li, Jun Zhu

We present Mixture of Contrastive Experts (MiCE), a unified probabilistic clustering framework that simultaneously exploits the discriminative representations learned by contrastive learning and the semantic structures captured by a latent mixture model.

Clustering Contrastive Learning +1

Countering Noisy Labels By Learning From Auxiliary Clean Labels

no code implementations • 23 May 2019 • Tsung Wei Tsai, Chongxuan Li, Jun Zhu

We consider the learning from noisy labels (NL) problem which emerges in many real-world applications.