在15.099课程中，大部分的课时由学生来领导，使用学生自己做的达到学术会议标准的陈述报告。课程阅读围绕这学期的主题：确定性最优化的随机方法。

Students lead most of the class sessions in 15.099, using the conference-quality presentations they have created. Course readings revolve around this term's topic, randomized methods for deterministic optimization.

与过去20多年的传统一致，最优化书报讨论课程的重点将放在麻省理工学院一部分最优化团体感兴趣的一个高级主题上：确定性最优化的随机方法。传统的最优化算法中迭代的计算和分析是确定的，与之相比，随机方法依靠随机过程和随机数字/向量的生成作为算法和（或）算法分析的一部分。在这个讨论会中，我们将会研读关于这个主题的一些新近的文章，其中很多作者是麻省理工学院的老师，同时我们也会研读已有文献中的一些旧文章，这些文章直到现在才引起人们的关注。

In keeping with the tradition of the last twenty-some years, the Readings in Optimization seminar will focus on an advanced topic of interest to a portion of the MIT optimization community: randomized methods for deterministic optimization. In contrast to conventional optimization algorithms whose iterates are computed and analyzed deterministically, randomized methods rely on stochastic processes and random number/vector generation as part of the algorithm and/or its analysis. In the seminar, we will study some very recent papers on this topic, many by MIT faculty, as well as some older papers from the existing literature that are only now receiving attention.