Publication Date
5-2013
Abstract
We show how group-theoretic ideas can be naturally used to generate efficient algorithms for scientific computations. The general group-theoretic approach is illustrated on the example of determining, from the experimental data, the dissociation constants related to multiple binding sites. We also explain how the general group-theoretic approach is related to the standard (backpropagation) neural networks; this relation justifies the potential universal applicability of the group-theoretic approach.
Comments
Technical Report: UTEP-CS-13-28