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目录 Proximal minimization 解释 Gradient flow 解释1 最大最小算法 不动点解释 Forward-backward 迭代解释 加速 proximal gradient method 交替方向方法 ADMM 解释1 自动控制 解释2 Augmented Largranians 解释3 Flow interpretation 解释4 不动点 特别的情况 Proximal Algorithms 这一节介绍了一些利用proximal的算法. Proximal mini…
Recently I systematicall review some sorting algorithms, including insertion sort, bubble sort, merge sort and quick sort. I then implement them in C++. All the function takes in a  vector<int>& type and directly operates on the input. To use th…
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More important than algorithms(just problems #$!%), the techniques/concepts residing at the base of such algorithms is more important. There are broadly 4 ways in which classification of algorithms can be done. Classification by purpose Each algorith…
Awesome Algorithms A curated list of awesome places to learn and/or practice algorithms. Inspired by awesome-awesomeness and all the other awesome Awesome libraries. If you want to contribute, please read the [contribution guidelines] (https://github…
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In this post we take a tour of the most popular machine learning algorithms. It is useful to tour the main algorithms in the field to get a feeling of what methods are available. There are so many algorithms available and it can feel overwhelming whe…
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1. Introduction Much like Newton's method is a standard tool for solving unconstrained smooth minimization problems of modest size, proximal algorithms can be viewed as an analogous tool for nonsmooth, constrained, large-scale, or distributed version…