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What's the dominant in the text is just the stuff, the stuff in his knapsack listed with as little implication as possible.
主题占支配地位，重要的是那些在背包里几乎没有任何含义的东西。
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Of course, all these items in the knapsack are evocative and what they do is they suggest a plot.
而这些东西都能唤起士兵的回忆和感情,它们作为线索。
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And so you could construct all subsets, check that the weight is less than the weight of the knapsack, and then choose the subset with the maximum value.
因此你可以构建所有子问题，判断它的重量,是否小于背包的重量，然后选择值最大的子问题。
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It's a list of the contents of the knapsack of a soldier during the Vietnam War, just a list of the contents.
故事讲述了一个越战士兵,背包里的东西，只是一系列东西而已。
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So I haven't done magic, I've given you a really fast way to solve a knapsack problem, but it's still exponential deep down in its heart, in something.
所以我并没有施魔法，我已经告诉了你,一种快速解决背包问题的方法了,但是某些方面它的核心仍然是指数增长的。
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But don't worry about it, it's not, I'm just using it because it's a simpler example than the one I really want to get to, which is knapsack.
但是别担心，我讲这些是因为它比我,真正想讲的问题简单一些，我想讲的是背包问题。
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So how long it takes to run is related to how many items I end up being able to fit into the knapsack.
所以，运行的时间是和我能够,装进背包的物品数目有关的。
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Let's now go back and instantiate these ideas for the knapsack problem we looked at last time In particular, for the 0-1 knapsack problem.
让我们回来用具体例子,来说明我们上次看过的背包问题,特别是对0-1背包问题来说。
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But let's look for a slight variant of it, where greedy is not so good. And that's what's called the zero-one knapsack problem.
但是让我们找一找它的一些变种，在这些变种中贪婪算法用处不大,这些问题也就是0/1背包问题。
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So we'll start looking in detail at one problem, and that's the knapsack problem. Let's see.
让我们开始仔细讲讲一个问题，那就是背包问题。
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with the continuous knapsack problem as we've formulated it, greedy is good.
因为正如我们已经归越过的,对于一般连续性背包问题贪婪算法很实用。
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So let's look at an example of a zero-one knapsack problem.
我们要像之前一样将其最优化,现在让我们来看一个0/1背包问题的例子。
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STUDENT: You can't exceed the volume that the knapsack can hold.
学生：你不能超过背包,所能容纳物品的体积。
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Typically up till now, we've looked at things that can be done in sublinear time. Or, at worst, polynomial time. We'll now look at a problem that does not fall into that. And we'll start with what's called the continuous knapsack problem.
至今为止我们已经处理过,亚线性问题，最多也就是多项式问题,我们现在要看的问题则是不能用这些解决的,我们将要开始讲连续背包问题。
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