Abstract:
Poisson inverse problems arise in many real-world applications, such as positron emission tomography and astronomical image deblurring. Expectation maximization (EM) is a standard---and perhaps the most popular---approach to solving a Poisson inverse problem. Vardi et al. proved EM asymptotically converges more than three decades ago; however, it was unclear how fast EM converges. In this talk, I will present a simple non-asymptotic convergence guarantee for EM. Our analysis exploits an interesting connection between EM and a portfolio selection method due to Cover
2020-10-12 16:00 ~ 2020-10-12 17:00
李彥寰 合聘教授(國立臺灣大學資訊工程學系與應用數學科學研究所)
綜三館R101