特邀英国布鲁内尔大学的Asoke Nandi教授做题为Degree Estimation from Noisy Polynomial Data via Time-series Modelling的报告，智信讲堂第5期将于2021年4月23日（周五）16:30-17:30通过ZOOM平台线上举行。 更多阅读欢迎参加！
参会密码：960195
This lecture has particular relevance to data science (mathematics, computer science, and electrical engineering). It is based on refereed research results that have been published very recently, i.e., over the last 12 months. It is relevant for polynomial regression. An accurate estimation of the polynomial degree is essential for better detection, estimation, and prediction. This will demonstrate how the degree of a polynomial can be estimated in a completely novel way and more successfully. The starting point is uniformly sampled polynomial data, the degree and the coefficients of the polynomial are unknown. The first part deals with noise-free data, while the second part deals with noisy data. 更多阅读
