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Foil 66 NP Completeness and Neural Networks In Summary

From Physical Optimization and Physical Computation CPSP713 Case studies in Computational Science -- Spring Semester 1996. by Geoffrey C. Fox
Neural Networks work well for data decomposition as neural variables are natural nonredundant description
In "analogous" TSP and navigation problems, constraints on redundant neural variable Þ elastic net (can view as a generalized neural net) better
Why do all methods work so well for graph partitioning when computer scientists are taught to be terrified by such NP complete problems

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