Give a real-world example in which one of the following computational problems appears: sorting, determining the best order for multiplying matrices, or finding the convex hull.
- 用到排序的应用很多，比如电商网站对商品按价格进行排序
- 关于矩阵相乘，我们需要找到最优的运算次数最少的运算次序，矩阵相乘在人工智能上用到很多
- [From Wiki]The problem of finding convex hulls finds its practical applications in pattern recognition, image processing, statistics, geographic information system, game theory, construction of phase diagrams, and static code analysis by abstract interpretation. It also serves as a tool, a building block for a number of other computational-geometric algorithms such as the rotating calipers method for computing the width and diameter of a point set. also application in CV.
Other than speed, what other measures of efficiency might one use in a real-world setting?
内存使用，资源占用（网络，磁盘等） Memory requirement, Degree of parallelism, Resource use( cpu or gpu cycles, Disk IO etc), Accessibility(Cloud/local)
Select a data structure that you have seen previously, and discuss its strengths and limitations.
数组，访问速度快，不能动态调整大小.
How are the shortest-path and traveling-salesman problems given above similar? How are they different?
- 相同点：都是在图中找一条路径
- 不同点：最短路径只是求2个点之间的路径，但是旅行商问题要遍历全部点并且回到起点，是一个全排列问题.
- In travelling salesman problem we want to know an order of delivery of stops that yields "lowest overall distance" travelled .
- This "lowest overall distance" is similar to shortest path finding situation .
- Shortest path is polynomially solvable but travelling -salesman is NP-Complete
Come up with a real-world problem in which only the best solution will do. Then come up with one in which a solution that is "approximately" the best is good enough.
这题好抽象 0 0 求根如果是无理数近似就行了找不到最优的.
Follow @louis1992 on github to help finish this task.