News

IEEE1mon
Target-Embedding Autoencoder With Knowledge Distillation for Multi-Label Classification
In the task of multi-label classification, it is a key challenge to determine the correlation between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most TEA-based ...
GitHub1mon
ek-usc/Evaluating-Autoencoder-Driven-Dimensionality-Reduction-for-Bulk-RNA-seq-Clustering-of-Green-Anole-Sk - GitHub
This project examined whether a deep autoencoder embedding could improve clustering of bulk RNA-seq data from green anole # muscle stem cells (MuSCs) relative to standard methods. Using features of ...
IEEE1y
Target-Embedding Autoencoder With Knowledge Distillation for Multi-Label Classification - IEEE Xplore
In the task of multi-label classification, it is a key challenge to determine the correlation between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most TEA-based ...