谌稳固 研究员（北京应用物理与计算数学研究所）

马俊杰 副研究员

Sparse Representation and Recovery of Sparse Signals

5月14日（周四）10:00-11:00，思源楼813

The sparse representation theory and non-convex optimization play important roles in compressed sensing and machine learning. In this talk, I will focus on the sparse decomposition of signals and some applications in recovery of sparse signals via non-convex minimization.

报告人简介：谌稳固，北京应用物理与计算数学研究所研究员，博士生导师，主要从事调和分析、压缩感知、机器学习、大数据分析的理论及应用研究，在IEEE Transactions on Information Theory, Applied and Computational Harmonic Analysis，Inverse Problems, SIAM Journal on Imaging Sciences, Journal of Machine Learning等学术期刊发表科研论文80余篇。