Fine-tuning pre-trained neural network models has become a widely adopte...
We propose a fine-tuning algorithm for brain tumor segmentation that nee...
Due to the expensive costs of collecting labels in multi-label classific...
Weakly supervised multi-label classification (WSML) task, which is to le...
We consider information-theoretic privacy in federated submodel learning...
In recent years, deep neural networks (DNN) have become a highly active ...
We introduce a variation of coded computation that ensures data security...
Deep neural networks(NNs) have achieved impressive performance, often ex...
Given multi-platform genome data with prior knowledge of functional gene...
How can we find patterns and anomalies in a tensor, or multi-dimensional...
We propose a novel technique to make neural network robust to adversaria...