Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Lifted inference approaches exploit symmetries of a graphical model. So far, only the automorphism group of the graphical model has been proposed to formalize the symmetries used.  show that this is only the GI-complete tip of a hierarchy and that the amount of lifting depends on how local the inference algorithm is: if the LP relaxation introduces constraints involving features over at most k variables, then the amount of lifting decreases monotonically with k. This induces a hierarchy of lifted inference algorithms, with lifted BP and MPLP at the bottom and exact inference methods at the top. In beten, there are relaxations whose liftings are equitable partitions of intermediate coarseness, which all can be computed in polynomial time.
['Martin Mladenov', 'Kristian Kersting']
I am writing a research paper on a idea Lifted inference via k-locality
[{"from": "human", "value": "I am writing a research paper on a idea Lifted inference via k-locality"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Lifted inference approaches exploit symmetries of a graphical model. So far, only the automorphism group of the graphical model has been proposed to formalize the symmetries used.  show that this is only the GI-complete tip of a hierarchy and that the amount of lifting depends on how local the inference algorithm is: if the LP relaxation introduces constraints involving features over at most k variables, then the amount of lifting decreases monotonically with k. This induces a hierarchy of lifted inference algorithms, with lifted BP and MPLP at the bottom and exact inference methods at the top. In beten, there are relaxations whose liftings are equitable partitions of intermediate coarseness, which all can be computed in polynomial time."}]