Genetic Improvement for Approximate Computing

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Sekanina:2016:WAPCO,

• author = "Lukas Sekanina and Zdenek Vasicek",
• title = "Genetic Improvement for Approximate Computing",
• booktitle = "2nd Workshop On Approximate Computing (WAPCO 2016)",
• year = "2016",
• editor = "George Karakonstantis and Costas Bekas and Dimitris Gizopoulos and Nikolaos Bellas",
• address = "Prague",
• month = jan # " 20",
• keywords = "genetic algorithms, genetic programming, Genetic Improvement, median",
• URL = "http://wapco.inf.uth.gr/papers/SESSION2/wapco2016_2_5.pdf",
• size = "2 pages",
• abstract = "This paper connects the Genetic Improvement (GI) method, recently established in the search-based software engineering community, with approximate computing, in order to obtain improvements in the cases when errors in computations can be tolerated. It is argued that Genetic Improvement which shares many objectives with the approximate computing can easily be adopted to solve typical problems in the area of approximate computing. An open problem is whether GI-based methodology can really be accepted by the approximate computing community.",
• notes = "gismo http://wapco.inf.uth.gr/index.html In conjunction with HiPEAC 2016",

}

Genetic Programming entries for Lukas Sekanina Zdenek Vasicek

Citations