Unsupervised Learning from Sequential Data with Recurrent Neural Networks
Project
Unsupervised Learning from Sequential Data with Recurrent Neural Networks
Principal Investigator
Harvard's School of Engineering and Applied Sciences
Summary
We investigate unsupervised or lightly-supervised methods and algorithms to uncover structure in sequential data. Our main focus is on parsing natural language, especially to transfer parsers from one language to another, thereby leveraging structure shared across languages to reduce the amount of necessary labelled data.