Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  prove under a plausible complexity hypothesis that Reduced Error Pruning of branching programs is hard to approximate within log1-δ n, for every δ > 0, where n is the number of description variables, a measure of the problem's complexity. The result holds under the assumption that NP problems do not admit deterministic, slightly superpolynomial time algorithms: NP ⊄ TIME(|I|O(loglog |I|)). This improves on a previous result that only had a small constant inapproximability ratio, and puts a fairly strong constraint on the efficiency of potential approximation algorithms. The result also holds for read-once and µ-branching programs.
['Richard Nock', 'Tapio Elomaa', 'Matti Kääriäinen']
I am writing a research paper on a idea Reduced error pruning of branching programs cannot be approximated to within a logarithmic factor
[{"from": "human", "value": "I am writing a research paper on a idea Reduced error pruning of branching programs cannot be approximated to within a logarithmic factor"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  prove under a plausible complexity hypothesis that Reduced Error Pruning of branching programs is hard to approximate within log1-\u03b4 n, for every \u03b4 > 0, where n is the number of description variables, a measure of the problem's complexity. The result holds under the assumption that NP problems do not admit deterministic, slightly superpolynomial time algorithms: NP \u2284 TIME(|I|O(loglog |I|)). This improves on a previous result that only had a small constant inapproximability ratio, and puts a fairly strong constraint on the efficiency of potential approximation algorithms. The result also holds for read-once and \u00b5-branching programs."}]