报告题目: |
请注意报告地点变化Optimality Conditions and a Smoothing Trust Region Newton Method for Non-Lipschitz Optimization |
报告人: |
袁亚湘 |
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中科院院士，前任中国运筹学会理事长（现为学会的名誉理事长）
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报告时间: |
2013-04-18 14:00 |
报告地点: |
舜德楼北412演讲厅 |
主办单位: |
清华大学工业工程系 |
简介: |
Regularized minimization problems with nonconvex, nonsmooth, perhaps non-Lipschitz penalty functions have attracted considerable attention in recent years, owing to their wide applications in image restoration, signal reconstruction and variable selection. In this talk, we derive affine-scaled second order necessary and sufficient conditions for local minimizers of such minimization problems. Moreover, we propose a global convergent smoothing trust region Newton method which can find a point satisfying the affine-scaled second order necessary optimality condition from any starting point. Numerical examples are given to demonstrate the effectiveness of the optimality conditions and the smoothing trust region Newton method.
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