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Towards Interpretable Dispatching Rules: Application of Expression Simplification Methods.

, , and . SSCI, page 1-8. IEEE, (2021)

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Operating System Core as Template for Embedded System Software Development., and . ICINCO (1), page 589-594. SciTePress, (2012)Combining Evolutionary Computation and Algebraic Constructions to Find Cryptography-Relevant Boolean Functions., , , and . PPSN, volume 8672 of Lecture Notes in Computer Science, page 822-831. Springer, (2014)Comparison of schedule generation schemes for designing dispatching rules with genetic programming in the unrelated machines environment., and . Appl. Soft Comput., (2020)On the evolution of bent (n, m) functions., , and . CEC, page 2137-2144. IEEE, (2017)Comparison of solution representations for scheduling in the unrelated machines environment., and . MIPRO, page 1336-1342. IEEE, (2016)Analyzing gene expression data: Fuzzy decision tree algorithm applied to the classification of cancer data., , and . FUZZ-IEEE, page 1-8. IEEE, (2015)On using genetic algorithms for intrinsic side-channel resistance: the case of AES S-box., , , , , and . CS2@HiPEAC, page 13-18. ACM, (2014)Comparison of ensemble learning methods for creating ensembles of dispatching rules for the unrelated machines environment., and . Genet. Program. Evolvable Mach., 19 (1-2): 53-92 (2018)Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions., , , and . CoRR, (2023)Evolving Cryptographic Pseudorandom Number Generators., , , , , and . PPSN, volume 9921 of Lecture Notes in Computer Science, page 613-622. Springer, (2016)