This upcoming fall, I am teaching a special topics course at the Math Department in MIT, called Topics in Mathematics of Data Science. This will be a mostly self-contained research-oriented course focusing on the theoretical aspects of algorithms that aim to extract information from data.

I have divided the content of the class in ten topics (or “lectures”), I’ll describe them below. The biggest novelty perhaps is that I have decided to present a number of **open problems** on each of these lectures. Given that this list of problems (and their description) may be of interest to the readers of this blog, I plan to include short versions of the lecture notes as blog posts (linking to the proper lecture notes) and include a description of a total of forty open problems over the course of ten future posts. I am hoping interesting discussions about some of these problems arise from comments on these posts!

This “post zero” serves as an announcement for the class (*if you are a student at MIT, think about taking the class!*) and a warm-up for the open problems, I am including two below. But first, the content of the class:

Continue reading 10 Lectures and 42 Open Problems in Mathematics of Data Science →