时间：2017年3月17日 中午11:30-12:10

地点：华中科技大学创新研究院恩明楼813室

报告人：李嘉 Postdoctoral Research Associate, Department of Mathematical Science, Rensselaer Polytechnic

Institute.

Title: Sparse approximation and data processing

Abstract: In scientific research, sparse approximation scheme has been widely applied to various data processing problems. In this presentation, I will briefly summarize my previous work in utilizing

sparse approximation and designing novel wavelet frame or low-rank regularization based image restoration, medical imaging, surface reconstruction, and semi-supervised learning models, which can be enhanced by advanced regularizations such as big-data-driven regularization, or extended to broader range of data processing in future. Moreover, I willalso present my research interest in approximation theory to build up the connection between wavelet frame methods and variation based methods,which would be important to validate the feasibility wavelet frame in high dimensional or non-Euclidean spaces.