Symbolic Learning for Improving the Performance of Transversal-Computation Algorithms
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DOI: 10.1109/access.2019.2895296
Abstract: Using the hypergraphs as the central data structure in dynamic discrete association problems is a common practice. The computation of minimal transversals (i.e., the family of all minimal hitting sets) in those hypergraphs is a… read more here.
Keywords: computation algorithms; transversal computation; symbolic learning; computation ... See more keywords
An Information Theoretic Approach to Symbolic Learning in Synthetic Languages
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DOI: 10.3390/e24020259
Abstract: An important aspect of using entropy-based models and proposed “synthetic languages”, is the seemingly simple task of knowing how to identify the probabilistic symbols. If the system has discrete features, then this task may be… read more here.
Keywords: synthetic languages; information theoretic; theoretic approach; learning synthetic ... See more keywords