Here is a long list of sources I consulted at various points while doing research for this project. As it might have become clear through reading the previous installments of this series, this was more a talk about the densest subgraph problem than it was about theory being useful in computer science. There are a few reasons for that, which I might explain in more detail at some point in the future1.

In Part 3, we discussed the densest subgraph problem (DSP) and some algorithms for solving it. In this section, we’ll be looking at how we can generalize this problem and those algorithms to solve some other problems. This is the part of the talk where I will introduce some fancy new math I had to learn in order to understand how one might generalize iterative peeling to solve adjacent problems.

One of the things that has been repeatedly drilled into me over the past year or so is the fact that if you want people to do things for you, you’re most likely going to have to harass them. (I don’t mean literal harassment, by the way – please don’t commit a criminal offense and say I encouraged you.) This is true especially when working with highly busy people like managers and professors.

I keep coming across articles (and occasionally videos, and occasionally fiction or poetry) online that I want to share and comment on, but I recently realized that I will never have time to fully comment on everything I read that I find interesting. So I’m pulling another page out of Cory Doctorow’s book: here is a dump of links to cool stuff, along with some (hopefully very) brief descriptions of why I found these articles interesting.

Last summer, I was tasked with writing a report about the research I completed and submitting it to my supervisor by the end of the summer. I, of course, had never done this kind of writing before, so I learned several lessons. The hard way. The learning process was super painful, but it did come in handy when I had to write two other research reports in my classes last fall.