Efficiently Learning Ising Models on Arbitrary Graphs [STOC’15]

The paper [1] presented in this blog is from Professor Guy Bresler at Massachusetts Institute of Technology. It was originally presented at the 47th Annual Symposium on the Theory of Computing (STOC, 2015). The paper mainly talks about how to reconstruct a graph with an Ising model given i.i.d data samples. Without any restrictive constraints… Continue reading Efficiently Learning Ising Models on Arbitrary Graphs [STOC’15]