主 講 人：胡膺期 教授（Chair Professor, Department of Information Systems, Business Statistics and Operations Management Hong Kong University of Science and Technology）
時 間：106年3月14日（星期二）上午10:00 ~ 11:50、下午14:00 ~ 15:50
地 點：中央大學 管理二館-311室
茶 會：上午 9:30 ~ 10:00
地 點：鴻經館 510 室
- 上午講題：An Outsider’s Review of Deep Learning - Part I
ABSTRACT
It seems that everyone is talking about deep learning. People appreciate the past successes on speech recognition, image processing, as well as theoretical advances made by deep learning and thus have great hope for its potential and future impact on data science. In this talk, I will review deep learning from a statistician's point of view. The focus is on insightful ideas from deep learning, specially those unfamiliar to statisticians.
- 下午講題：An Outsider’s Review of Deep Learning – Part II
ABSTRACT
I will review a couple of specific neural networks that are extremely successful in their intended applications. The convolution networks and recurrent networks have been successfully applied to image data and sequential data, respectively. Thus they are worthy of special attention not only because of their long established successes in practice but also because they probably represent two fundamental aspects of learning, one with a prominent space component and the other with a prominent time component. One of the goals of this review is to explain the ideas empowered by these two types of neural networks.
