# 18.S096: Community dection and the Stochastic Block Model

A new set of lecture notes is available here about community detection and recovery in the stochastic block model, including five open problems . As usual, I will document the open problems here, while referring a much more detailed description of the problems on the notes, including description of partial progress.

Open Problem 9.1. (Detection Threshold for SBM for three of more communities)

What is the partial recovery threshold for the Stochastic Block Model on $k\geq 3$ communities.

Open Problem 9.2. (Recovery Threshold for SBM for logarithmic many communities)

What is the exact recovery threshold for the Stochastic Block Model with a logarithm number of communities? Both computational and information theoretical.

Open Problem 9.3. (Tightness of k-median LP)

Is the k-medians Linear Programming relaxation tight even for point clouds coming from generative models that do not have a community structure?

Open Problem 9.4. (Stability conditions for tightness of k-median LP and k-means SDP)

Can one give conditions for integrality of the k-medians LP or the k-means SDP based on stability type properties (on the fact that the data is “well-explained” by a certain number of clusters)?

Open Problem 9.5. (Positive PCA tightness)

Is the Semidefinite programming relaxation for the positive Principal Component Analysis problem tight with high probability for Wigner matrices?