When Deep Learning Meets Transfer Learning

Abstract

Deep learning has achieved great success as evidenced by many practical applications and contests. However, deep learning developed so far also has some inherent limitations. In particular, deep learning is not yet very adaptable to different related domains and cannot handle small data. In this talk, I will give an overview of how transfer learning can help alleviate these problems. In particular, I will present some recent progress on integrating deep learning and transfer learning together and show some interesting applications in sentiment analysis, image processing and urban computing.