Last week, USC hosted our annual Southern California Network Economics and Game Theory (NEGT) workshop. (Thanks to David Kempe and Shaddin Dughmi for all the organization this year!) It’s always a very fun workshop, and really does a great job in ensuring a multidisciplinary community around CS, EE, and Econ in the LA area. We’ve been doing it for so long now that the faculty & students really know each other well at this point…
As always, there were lots of great talks. In particular, we had a great set of keynotes again this year.
At long last, we have gotten together and created a “Caltech-style” machine learning / big data / optimization group, and it’s called DOLCIT: Decision, Optimization, and Learning at the California Institute of Technology. The goal of the group is to take a broad and integrated view of research in data-driven intelligent systems. On the one hand, statistical machine learning is required to extract knowledge in the form of data-driven models. On the other hand, statistical decision theory is required to intelligently plan and make decisions given imperfect knowledge. Supporting both thrusts is optimization. DOLCIT envisions a world where intelligent systems seamlessly integrate learning and planning, as well as automatically balance computational and statistical tradeoffs in the underlying optimization problems.
In the Caltech style, research in DOLCIT spans traditional areas from applied math (e.g., statistics and optimization) to computer science (e.g., machine learning and distributed systems) to electrical engineering (e.g., signal processing and information theory). Further, we will look broadly at applications spanning information and communication systems to the physical sciences (neuroscience and biology) to social systems (economic markets and personalized medicine).
In some sense, the only thing that’s new is the name, since we’ve been doing all these things for years already. However, with the new name will come new activities like seminars, workshops, etc. It’ll be exciting to see how it morphs in the future!
(And, don’t worry, RSRG is still going strong — RSRG and DOLCIT should be complementary with their similar research style but differing focuses with respect to tools and applications.)