Renzhen Wang

Imbalanced Semi-supervised Learning with Bias Adaptive Classifier

2022 · arXiv (Cornell University)

Pseudo-labeling has proven to be a promising semi-supervised learning (SSL) paradigm. Existing pseudo-labeling methods commonly assume that the class distributions of training data are balanced. However, such an assumption is far from realistic scenarios and …

Learning Representations from Local to Global for Fine-grained Patient Similarity Measuring in Intensive Care Unit

2022 · 2022 IEEE International Conference on Data Mining (ICDM)

Patient similarity measurement is an essential step in discovering clinically meaningful subgroups and building case retrieval systems. Most existing studies implement this procedure using similarity measurement algorithms on the multivariate clinical time-series (input space) or …