Bridging the theory and practice: A unified statistical and optimization perspective
- 2018-02-26 (Mon.), 10:30 AM
- 中研院-統計所 2F 交誼廳
- 茶 會:上午10:10統計所二樓交誼廳
- 李彥寰先生
- ?cole Polytechnique F?d?rale de Lausanne
Abstract
Despite many exciting empirical successes in data science, there are significant gaps between theory and inspired-by-theory practices. For example, the standard lasso (\ell_1-penalized least squares regression) is not appropriate for variable selection in non-linear statistical models; uniformly random sampling suggested by theory is not adopted in practical compressive medical imaging; the standard bounded gradient/curvature condition in convex optimization just does not hold in some crucial applications. In this talk, I will present how we addressed these gaps—rigorously—via identifying more general conditions on the problem settings, or even developing completely new theoretical frameworks.
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