What's the complexity of this algorithm?
这个算法的复杂度又是多少呢？
This algorithm is one of my operation.
这个算法是我的一个作业。
Clearly, this algorithm runs in o (mn) time.
显然，这个算法的运行时间为O (mn)。
The KerberosKey class implements this algorithm.
KerberosKey类实现了这种算法。
Well how many more steps does this algorithm take?
用同样的算法需要多几个步骤？
The correctness of this algorithm is intuitively clear.
这种算法的正确性是很显然的。
This algorithm is not perfect and certain edge cases exist.
这个算法并不是很完美，并存在某些边缘情况。
Of course, this algorithm probably raises more questions than it answers.
当然，与这个算法解决的问题相比，它导致的新问题可能更多。
Experiment results validate validity and limitation of this algorithm.
实验结果验证了该算法的有效性和局限性。
Through this algorithm, the file compression can achieve very good results.
通过这个算法，能对文件压缩达到很好的效果。
This algorithm assigns a relative influence score and passivity score to every user.
该算法定义了每个用户的消极性分值和影响力分值。
Several Google engineers have posted publicly that they're working on this algorithm.
一些Google的工程师已经公开承认他们目前正在努力完成这一算法。
If the dataset has duplicates, this algorithm automatically falls back to random mode.
如果是有重复的数据集，该算法就会自动转到随机模式。
In this algorithm, the order in which buffers get processed is much less deterministic.
在这个算法中，处理缓冲区的次序是很不确定的。
This algorithm type is quite common in search databases and other reference applications.
在搜索数据库和其他参考应用程序里，这种算法类型相当普遍。
This algorithm can take into account different capacities for different endpoints in a group.
这个算法能够考虑到组中不同端点的接受能力。
Implementing and executing this algorithm using our libraries produced the following results.
使用我们的库来实现并执行这个算法产生以下结果。
This algorithm repeats recursively until all newly resolved subgroups have no further subgroups.
此算法递归地重复，直到所有新解析的子组不再包含子组。
This algorithm repeats recursively until all newly resolved subgroups contain no further subgroups.
此算法递归地重复，直到所有新解析的子组不再包含子组。
This algorithm style will produce a tree whose leaves are defined by tasks that take the THEN branch.
该风格的算法将生成一棵树，其中树叶由采用THEN分支的任务定义。
It's easy to see that this algorithm always works if the maze you're in has an entrance and an exit on its border.
很容易看出，如果迷宫的边界上有一个入口和一个出口，那么这种算法总是有效的。
This algorithm tends to be memory efficient (allocating what's necessary) but requires more time to manage the heap.
这种算法通常具有较高的内存使用效率(分配需要的内存)，但是却需要花费更多时间来对堆进行管理。
I ask you for the running time of this algorithm and you give me the running time in terms of the running time, right.
我需要得到此算法的时间复杂度，那就明确地给出其，运行时间。
This algorithm can be a little hard to read for anyone who is unfamiliar with Erlang syntax and/or not paying attention.
不熟悉Erlang语法或者不留心听讲的话，上面的算法读起来有点难懂。
I was hoping to implement this algorithm completely in this column, but I have had to invest some time in learning JUnit.
我希望在这篇专栏文章中完整地实现该算法，但我必须花一些时间来了解JUnit。
The constraint of this algorithm is that a local element is not allowed to be declared with the same name of a global element.
这个算法的限制是局部元素不能声明为与全局元素同名。
It wasn't acknowledged that this algorithm was based on the SuperMemo one; I had to ask a question on the forums to get an answer to that.
这里没有讲到这个算法是来自于supermemo；我不得不在它的论坛上提问来寻求答案。
They reserve the right to tweak this algorithm whenever they feel it is necessary, often without warning or any obvious outside influence.
他们依然保留有调整这个算法的权利，只要他们觉得有必要，他们就会调整这个算法，通常都没有事先的警告，也不受外界的影响。
One downside to this algorithm is that it requires more math with big numbers, and thus is a little more computationally taxing on a busy server.
这个算法的缺点是需要计算更大的数字，所以对于一个很忙的服务器来说计算成本更大。
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