Results 221 to 230 of about 3,357,375 (267)
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SIAM Journal on Computing, 1999
Summary: Improving a long-standing result of \textit{A. Schönhage, M. Paterson}, and \textit{N. Pippenger} [J. Comput. Syst. Sci. 13, 184-199 (1976; Zbl 0333.68033)] we show that the median of a set containing \(n\) elements can always be found using at most \(c \cdot n\) comparisons, where ...
Dorit Dor, Uri Zwick
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Summary: Improving a long-standing result of \textit{A. Schönhage, M. Paterson}, and \textit{N. Pippenger} [J. Comput. Syst. Sci. 13, 184-199 (1976; Zbl 0333.68033)] we show that the median of a set containing \(n\) elements can always be found using at most \(c \cdot n\) comparisons, where ...
Dorit Dor, Uri Zwick
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Genetic Algorithm Guided Selection: Variable Selection and Subset Selection
Journal of Chemical Information and Computer Sciences, 2002A novel Genetic Algorithm guided Selection method, GAS, has been described. The method utilizes a simple encoding scheme which can represent both compounds and variables used to construct a QSAR/QSPR model. A genetic algorithm is then utilized to simultaneously optimize the encoded variables that include both descriptors and compound subsets.
Sung Jin Cho, Mark A. Hermsmeier
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SSRN Electronic Journal, 2000
AbstractThis paper studies how schooling admission tests affect economic performance in an economy where individuals are endowed with both academic and non‐academic abilities and both abilities matter for labour productivity. We develop a simple model with schools run by the goverment, where individuals signal their abilities by taking an admission ...
GIANNINI, MASSIMO, Brunello, G.
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AbstractThis paper studies how schooling admission tests affect economic performance in an economy where individuals are endowed with both academic and non‐academic abilities and both abilities matter for labour productivity. We develop a simple model with schools run by the goverment, where individuals signal their abilities by taking an admission ...
GIANNINI, MASSIMO, Brunello, G.
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Journal of Algorithms, 1999
Sequential selection has been solved in linear time by Blum et al. [M.B. Blum, R.W. Floyd, V.R. Pratt, R.L. Rivest, R.E. Tarjan, Time bounds for selection, J. Comput. System Sci. 7 (4) (1972) 448-461 ]. Running this algorithm on a problem of size N with N > M, the size of the main-memory, results in an algorithm that reads and writes O(N) elements ...
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Sequential selection has been solved in linear time by Blum et al. [M.B. Blum, R.W. Floyd, V.R. Pratt, R.L. Rivest, R.E. Tarjan, Time bounds for selection, J. Comput. System Sci. 7 (4) (1972) 448-461 ]. Running this algorithm on a problem of size N with N > M, the size of the main-memory, results in an algorithm that reads and writes O(N) elements ...
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Behavioral and Brain Sciences, 1981
AbstractHuman behavior is the joint product of (i) contingencies of survival responsible for natural selection, and (ii) contingencies of reinforcement responsible for the repertoires of individuals, including (iii) the special contingencies maintained by an evolved social environment.
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AbstractHuman behavior is the joint product of (i) contingencies of survival responsible for natural selection, and (ii) contingencies of reinforcement responsible for the repertoires of individuals, including (iii) the special contingencies maintained by an evolved social environment.
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Proceedings of ICCI'93: 5th International Conference on Computing and Information, 2002
Lane A. Hemachandra +5 more
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Lane A. Hemachandra +5 more
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Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2021
William George La Cava, Thomas Helmuth
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William George La Cava, Thomas Helmuth
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