More fun at the theory festival: plenary sessions – guest post by Sanjeev Arora

Towards the business meeting, another personal post in our series (this one by Sanjeev Arora):

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An important part of the plan for theory festival —which everybody involved agrees upon—is the need for a substantial plenary component. The festival organizing committee would select the plenary program based upon inputs from various sources.

Plenary sessions will include about 20-25 short talks from a broad spectrum of “Theory” subcommunities, including (but not limited to) SODA, CCC, COLT, CRYPTO, KDD, EC, PODS, PODC, etc., as well as STOC and FOCS. We envisage some kind of nomination process whereby these communities/PCs could propose recent papers presented at their recent conferences which would be of interest to a broader theory audience. Sometimes they could nominate an older paper that is now generating a lot of work, or a survey talk.

Plenary sessions would also include 1-hr lectures introducing an area in science, social science, or mathematics of interest to a broad theory audience. I could’ve generate some sample topics myself, but in interest of fun I decided to ask for suggestions from a small group of people. (I’ve reworded/shortened their answers.)

Silvio Micali: Connectomics (figuring out the graph of interconnections of the brain’s neurons from imaging data).

Scott Aaronson: (a) Recent work connecting complexity, quantum information and quantum gravity (Harlow, Hayden, Preskill etc.); it is creating waves (b) Theorist-friendly introduction to deep nets and deep learning.

Ankur Moitra: Linear Inverse Problems: recovering an object from linear measurements (includes robust PCA, matrix completion, phase retrieval, tensor completion, etc. May have interesting connections to SDPs and other convex methods studied in our community.

Suresh Venkatsubramanian: (a) Computational Topology. Motivated by data analysis, it has completely taken over what used to be called computational geometry. STOC/FOCS people might be able to provide approximation algorithms for topological quantities. (b) Optimization: a basic primitive in many applied settings, especially machine learning. Esoteric optimization ideas like momentum and regularizers are now ubiquitous in applications, but haven’t affected STOC/FOCS world much (except for recent work on flows).

In your comments, please send other suggestions for talks that might be interesting.

Remember, the festival will also have a separate slot for technical tutorials on interesting topics within CS and theoretical CS. Also, some workshops may feature their own invited/plenary talks.

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