Tetsuo Shibuya

UDON: Unsupervised Data SelectiON for Biomedical Entity Recognition

2021

High-quality training datasets are critical for building successful Machine Learning (ML) based NLP systems. However, these datasets are not always available in low-resource contexts such as the biomedical domain. Here, selecting relevant training data is …

Privacy-Optimized Randomized Response for Sharing Multi-Attribute Data

2024

With the increasing amount of data in society, privacy concerns in data sharing have become widely recognized. Particularly, protecting personal attribute information is essential for a wide range of aims from crowdsourcing to realizing personalized …