A Review of Fast L1-Minimization Algorithms for Robust Face Recognition
2013-11-18 10:43
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A Review of Fast L1-Minimization Algorithms for Robust Face Recognition
@作一个算法工程师往往会碰到许多难题,尤其是数学问题.数学有很强的逻辑性.它需要你有很强的逻辑思维能力,抽象思维能力,符号表达的能力.而这些正是算法工程师头疼的地方.数学讲究它的严谨性,结论的得出是需要一步一步证明得来的.如果算法工程师能够证明出数学的结论,那他对算法的原理已经相当理解了.这,对我来说,是极其困难的.即使我能够熟记整个数学证明过程,我可能也无法理解数学当中的原理.所以,我想借助博客这个途径,跟广大各位博友一起学习算法,一起讨论算法,共同进步.@
liyuanhao1114@163.com
目录:
摘要:
1、介绍
1.1 注释
1.2 原对偶内点法
2、Fast L1-Min Algorithms
2.1 Gradient Projection Method
2.2 Homotopy Method
2.3 Iterative Shrinkage-Thresholding Methods
2.4 Proximal Gradient Methods
2.5 Augmented Lagrange Multiplier Methods
3、Simulation: Random Sparse Signals
未完待续......
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