Generating borderline test samples for randomness testers via intelligent optimization and evolutionary algorithms. [PDF]
Sci RepGao P, Zhang B, Wang Z, Li C.
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Multi-label active learning based on submodular functions
, 2018 Kuoliang Wu, Deng Cai, Xiaofei He
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Sampling via the aggregation value for data-driven manufacturing. [PDF]
Natl Sci Rev, 2022 Liu X +5 more
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Which submodular functions are expressible using binary submodular functions?
, 2016 Submodular functions occur in many combinatorial optimisation problems and a number of polynomial-time algorithms have been devised to minimise such functions. The time complexity of the fastest known general algorithm for submodular function minimisation (SFM) is O(n^6+n^5L), where n is the number of variables and L is the time required to evaluate ...
Živný, S, Jeavons, P
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A hybrid evolutionary algorithm for influence maximization in complex networks using invasive weed optimization and gravitational search. [PDF]
Sci RepLiu L, Xu J, Lai S, Trik M.
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Diversified-profit maximization in competitive social advertising. [PDF]
J Comb Optim, 2023 Du L, Gao S, Yang W.
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Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data. [PDF]
Brief BioinformLi Y +7 more
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Evaluation of combinatorial optimisation algorithms for c-optimal experimental designs with correlated observations. [PDF]
Stat Comput, 2023 Watson SI, Pan Y.
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Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization [PDF]
Yihang Gao, Vincent Y. F. Tan
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