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- W4384008237 abstract "The usual approach in runtime analysis is to derive estimates on the number of fitness function evaluations required by a method until a suitable element of the search space is found. One justification for this is that in real applications, fitness evaluation often contributes the most computational effort. A tacit assumption in this approach is that this effort is uniform and static across the search space. However, this assumption often does not hold in practice: some candidates may be far more expensive to evaluate than others. This might occur, for example, when fitness evaluation requires running a simulation or training a machine learning model." @default.
- W4384008237 created "2023-07-13" @default.
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- W4384008237 date "2023-07-12" @default.
- W4384008237 modified "2023-09-25" @default.
- W4384008237 title "Runtime Analysis with Variable Cost" @default.
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- W4384008237 doi "https://doi.org/10.1145/3583131.3590432" @default.
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