What is the genie here? Information theoretic approach to label detection??

Dabbling with a few ideas here ...

1.The true vs Ideal problem: What would be the best way to caste the optimal vector detection problem?

2.Information theoretic approach? Dr. Miguel’s ICML paper ... Seems attractive. But will the bounds result in any revelations?

3.Min-Cut + Random graph theory? Super combo!

4.Tree Network datasets ... What are some examples of organically derivable network datasets that happen to be tree-structured naturally. Now why am I interested? For LBP is exact on trees..