• So I'm going to solve this by enumerate and check, which is an example of what's called a brute-force algorithm.

    你懂的,所以我得靠列举和检验来解决这个问题,这就是我们说的穷举算法。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • And so the fact that in this whole slide here, this algorithm for sorting, I'm using the verb sort.

    在这个排序算法中,我用到了一个动词排序。

    哈佛公开课 - 计算机科学课程节选

  • A log algorithm typically is one where you cut the size of the problem down by some multiplicative factor.

    对数级复杂度的算法就是指,通过一系列常量级步数的操作,可以将问题的规模。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • It couldn't have been a very complicated algorithm because it basically paired people up randomly on the campus.

    这个算法不是很复杂,基本上是给校园里的人随机配对。

    耶鲁公开课 - 心理学导论课程节选

  • We started off talking about binary search, and I suggested that this was a log algorithm which it is, which is really kind of nice.

    我告诉了你们这是一个对,数级的算法,这是很棒的,我们来一起看看这个算法到底做了什么。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • And the obvious question I could start with is, and suppose I ask you, how long does the algorithm implemented by this program take to run?

    我开始这个话题的第一个问题是,假设我问你,由这个算法实现的程序大概,要运行多久才能给出答案?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • You might remember vaguely logarithms from high school math and such but what this suggests for us , the computer scientists, is that this is certainly a smarter, a faster algorithm.

    你可能还会依稀记得,高中数学里的对数,这就给了我们这些计算机科学家们,一些启示,即,这种算法更智能,更迅速。

    哈佛公开课 - 计算机科学课程节选

  • Obviously the algorithm is likely to depend on the size of the input, so this is not a great idea.

    很明显这个算法是与我的,输入的大小相关的,因此这不是个好方法。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • And that's because that is a version of a divide and conquer algorithm.

    这个想法非常重要,因为这就是分而治之算法的一个版本。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • So this is a nice little search-- sorry, a nice little sort algorithm . And in fact, it's relying on something that we're going to come back to, called the loop invariant.

    恩,这是一个很棒的小搜索,抱歉,和很棒的小排序算法,事实上,它依赖于一些我们要回顾的东西,被称作循环不变量。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • So what we want to do, is, I guess another way of saying it is, efficiency is really about choice of algorithm.

    因此我们想做的就是,换种说法,效率实际上是算法的选择,我们想要培养你们。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • Why don't I just keep track on each pass through the algorithm whether I have done any swaps?

    我为什么不仅仅跟踪算法的,每一遍来看看我做了哪些交换呢?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • All right? Because if I don't do any swaps on a pass through the algorithm, then it says everything's in the right order.

    好么?因为如果我,这一遍没有做任何交换,那么就意味着已经排好序了。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • I want you to recognize classes of algorithms and match what you see in the performance of the algorithm to the complexity of that algorithm. All right?

    让我再试一次这么说,我期望大家能通过,算法的复杂度,来看到算法的性能?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • And so you care-- you care about ultimately how much time is my algorithm gonna take to perform on that worst case running time.

    因此你最终所关心的是,算法在最坏情况下需要多长的,运行时间。

    哈佛公开课 - 计算机科学课程节选

  • They are computationally challenged, meaning, at the time they were invented, they were perfectly good sorting algorithms, there are better ones, we're going to see a much better one next time around, but this is a good way to just start thinking about how to do the algorithm, or how to do the sort.

    他们是相当棒的排序算法,是有更好的算法,我们下一次,就会看一个更好的,但是开始想想,如何完成算法,或者说是如何排序,是一个好的学习方法,恩,再试试吧,如何来排序呢?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • Well, we saw the teaser in terms of that animation that suggests this merge sort algorithm when implemented by a computer is absolutely faster.

    我们从前面的动画中可以看到,这个归并排序算法在计算机上实现之后,绝对比其他算法更快。

    哈佛公开课 - 计算机科学课程节选

  • Again, I want you to start seeing how to map the characteristics of the code- the characteristics of the algorithm, let's not call it the code-- to the complexity.

    是算法中的那些特性,我们还是别说代码了,转化为复杂度-,我一会儿还会再讲点儿这个的,但是我们再看一个例子。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • Alright, I have the problem so clearly this algorithm whatever it's gonna be is gonna be at least twice as fast because I'm doing half as much work.

    现在,这个问题已变得清晰,不管怎么样,排序算法的效率,至少是之前的两倍,因为我只需要做一半的工作。

    哈佛公开课 - 计算机科学课程节选

  • Where those pieces, I would do the same thing with, I would divide them up into smaller chunks, and sort those. Is that going to give me a more efficient algorithm?

    合并起来,而那些小列表,我又会把他们拆成更小的列表,再排序,这会给我,一个更高效的算法么?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • It's an example of a very common tool that's going to be really useful to us, not just for doing search, but for doing a whole range of problems. That is, in essence, the template the describes a log style algorithm.

    不仅仅是做搜索,还可以解决一整类问题,本质上,这个模板就描述了,对数形的算法,我们一会再回来。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • All right? I don't care what's in there, but just assume that's my list. And just to remind you, on your handout, and there it is on the screen, I'm going to bring it back up, there's the little binary search algorithm.

    好,我不管列表里是什么,就假定那是一个列表,要提醒你们的是,在你们的讲义上和屏幕上,有一个简单的二分查找算法。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • It will probably quit at some point because of space issues, unless I'm writing an algorithm that is using no additional space.

    其中一个的时候,它会一直运行下去,它可能在某一处因为空间问题退出,除非我写了一个。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • The algorithm doesn't know that it's going to take this long to compute, it's just busy crunching away, trying to see if it can make it happen.

    这很可能会发生,但是你知道的,算法本身并不知道,计算这个问题需要多长的时间,它就一直忙碌的算啊算。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • What is this? What category of algorithm is that? Somebody? Louder?

    这是什么呢?这种算法属于什么类别呢?,有人知道吗?大点声?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • Where have we implemented a greedy algorithm, or have been asked to do a greedy algorithm? Well, there are not that many things you guys have been working on this semester.

    现在你已经实施了一个贪婪算法,我们在哪里实施了贪婪算法,或者我们那里被要求实施贪婪算法呢?,们这学期不需要用什么功对吧?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • What is the class of algorithm that's- that probably applies to this, and how do I pull something out of that, if you like, a briefcase of possible algorithms to solve?

    以及哪种算法-,可能可以应用到这类问题上,问题本身又能提取出什么东西来,以及可能解决问题的一系列方法的简介?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • And you really, wherever possible, want to avoid that exponential algorithm, because that's really deadly. Yes.

    比你的电脑的性能增长的快多了,并且大家无论何时,都要避免去用指数级的函数。

    麻省理工公开课 - 计算机科学及编程导论课程节选

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