Last week, we trekked from Caltech over to UCLA for the Southern California Network Economic and Game Theory (NEGT) workshop. This was the fifth year for this event, which focuses on the intersection of CS, EE, and Economics. It rotates between USC, UCLA, and Caltech, and serves as a place where all the folks in the southern California area interested in topics at this intersection can get together and catch up. This year, Mihaela van der Schaar and Bill Zame did a great job of hosting at UCLA.
I must say that I really love this sort of regional workshop — it’s one of my favorite events of the year. We organize it with a bunch of faculty talks, pretty equally spilt across EE, CS, and Econ, and also pretty equally split across USC, UCLA, and Caltech. Then, we bring in a few keynotes from outside of southern CA to round things out. The quality of the talks is usually outstanding — and as a result, we tend to have 100+ people attend during the 2 days. But, the best part is that the conversations that get started at the workshop really tend to extend throughout the year. Since everyone is so close geographically, when common interests are discovered at the workshop, it tends to lead to multiple visits during the coming year… and since it’s been going on for five years now, we really have a community where folks in this area pretty much know everyone — regardless of the school and department they are from. The workshop has really created a large and vibrant algorithmic game theory community here in the LA area, and one that is pretty unique in the sense that it truly bridges the three fields. One thing that struck me this year was that it was often difficult to tell what department the speaker was from — by this point the topics & tools have really merged in our SoCal community. I think this is really a consequence of the success of NEGT.
This year’s workshop
This year, we were especially lucky to have Sanjeev Goyal and Ali Jadbabaie as our keynote speakers. Both talked about problems related to cascades on networks, but with very different perspectives and techniques, so it was interesting to contrast the two. In fact, there was a lot of other work presented on cascades this year, too. On the morning of the second day, we had back-to-back talks from Ali Sayed and Omer Tamuz, which were both focused on cascades of information over graphs, and specifically when learning and agreement are possible. But, Ali’s talk was from an EE perspective, focusing on formulations related to consensus problems, while Omer’s talk was more from the perspective of the herding literature in economics. (If you haven’t seen Omer’s work related to this topic, stop reading this now and go take a look — it is quite a tour-de-force: On agreement and learning. We’re all very excited that he’ll be joining Caltech’s Econ department soon.)
Seeing these two talks back-to-back really highlighted the fact that most venues related to algorithmic game theory are really dominated by CS and Economics, and rarely include many folks from the EE side. I think something is lost because of this. The EE side of things really brings strikingly different models and insights, and the algorithmic game theory area would certainly become richer through its inclusion. Another example of this at the workshop came from Edmund Yeh‘s talk. Edmund is from EE at Northeastern, but we were lucky enough to find that he was in the area and convince him to come take part in the workshop. He presented his recent work using tools from information theory (quantization) to help design mechanisms for pricing with limited information, which is (to my knowledge) one of the first applications of information theory tools to mechanism design. I think this is a tool set that is likely to find a lot of applications in the coming years…
Next year’s workshop
The downside of a rotating local workshop is that you have to host it every once in a while…and next year is that year for us at Caltech. So, if you are interested in coming to Pasadena next November, and want to take part in the sixth NEGT, let me know!