Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: First-order knowledge compilation techniques have proven efficient for lifted inference. They compile a relational probability model into a target circuit on which many inference queries can be ansred efficiently. Early methods used data structures as their target circuit. In our KR-2016 paper,  shod that compiling to a low-level program instead of a data structure offers orders of magnitude speedup, resulting in the state-of-the-art lifted inference technique. ,  conduct experiments to address two questions regarding our KR-2016 results: 1- does the speedup come from more efficient compilation or more efficient reasoning with the target circuit?, and 2- why are low-level programs more efficient target circuits than data structures?
['Seyed Mehran Kazemi', 'David Poole']
I am writing a research paper on a idea Why is Compiling Lifted Inference into a Low-Level Language so Effective?
[{"from": "human", "value": "I am writing a research paper on a idea Why is Compiling Lifted Inference into a Low-Level Language so Effective?"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: First-order knowledge compilation techniques have proven efficient for lifted inference. They compile a relational probability model into a target circuit on which many inference queries can be ansred efficiently. Early methods used data structures as their target circuit. In our KR-2016 paper,  shod that compiling to a low-level program instead of a data structure offers orders of magnitude speedup, resulting in the state-of-the-art lifted inference technique. ,  conduct experiments to address two questions regarding our KR-2016 results: 1- does the speedup come from more efficient compilation or more efficient reasoning with the target circuit?, and 2- why are low-level programs more efficient target circuits than data structures?"}]