If I'm running a linear algorithm, it'll take one microsecond to complete.

算法会在1微秒内完成，如果是一个平方级的方法。

麻省理工公开课 - 计算机科学及编程导论课程节选

Typical characterization, not all the time, but typical characterization, is an algorithm that reduces the size of a problem by one, or by some constant amount each time, is typically an example of a linear algorithm.

我们学习过了线性算法，它的典型特征，不是通用的,但是比较典型的特征是，它是逐一减小问题的大小的，或者说是每次减小常数的大小。

麻省理工公开课 - 计算机科学及编程导论课程节选

It is certainly possible, for example, that a quadratic algorithm could run faster than a linear algorithm. It depends on what the input is, it depends on, you know, what the particular cases are. So it is not the case that, on every input, a linear algorithm is always going to be better than a quadratic algorithm.

一个二次平方级复杂度的算法,当然也是可能跑的比线性复杂度算法快的,这取决于，你知道的，输入以及特定的案例，因此并不是对于每个输入,线性复杂度就一定会,比二次平方级复杂度的算法的表现要好,只是通常来说是这样的。

麻省理工公开课 - 计算机科学及编程导论课程节选

That algorithm is linear. You can see it.

是线性增长的。

麻省理工公开课 - 计算机科学及编程导论课程节选