Results 271 to 280 of about 708,932 (315)
SnRK2.6 phosphorylates sucrose transporter ZmSUT1 to enhance yield by modulating leaf senescence in maize. [PDF]
Sci AdvYang T +13 more
europepmc +1 more source
RF-SVR-based prediction methodology for metal tube-bending rebound: Handling non-uniformity and limited sample challenges. [PDF]
PLoS OneFang Z, Zhang P, Li L, Zhang Q.
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Integrated transcriptomic and metabolomic profiles analysis reveals a potential gene-metabolite network associated with anthocyanin-mediated color variation in maize kernels. [PDF]
Front Plant SciRan J +10 more
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Kernel Factory: An ensemble of kernel machines [PDF]
Expert Systems with Applications, 2013 We propose an ensemble method for kernel machines. The training data is randomly split into a number of mutually exclusive partitions defined by a row and column parameter. Each partition forms an input space and is transformed by an automatically selected kernel function into a kernel matrix K.
Michel Ballings, Dirk Van den Poel
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Multiple Kernel k-means with Incomplete Kernels [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Multiple kernel clustering (MKC) algorithms optimally combine a group of pre-specified base kernel matrices to improve clustering performance. However, existing MKC algorithms cannot efficiently address the situation where some rows and columns of base kernel matrices are absent.
Marius Kloft +2 more
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2011 International Conference on Computer Vision, 2011
Naive Bayes Nearest Neighbor (NBNN) has recently been proposed as a powerful, non-parametric approach for object classification, that manages to achieve remarkably good results thanks to the avoidance of a vector quantization step and the use of image-to-class comparisons, yielding good generalization.
Tinne Tuytelaars +3 more
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Naive Bayes Nearest Neighbor (NBNN) has recently been proposed as a powerful, non-parametric approach for object classification, that manages to achieve remarkably good results thanks to the avoidance of a vector quantization step and the use of image-to-class comparisons, yielding good generalization.
Tinne Tuytelaars +3 more
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Partitionable Kernels for Mapping Kernels
2011 IEEE 11th International Conference on Data Mining, 2011Many of tree kernels in the literature are designed tanking advantage of the mapping kernel framework. The most important advantage of using this framework is that we have a strong theorem to examine positive definiteness of the resulting tree kernels.
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Multiple kernel clustering with corrupted kernels
Neurocomputing, 2017Abstract Multiple kernel clustering (MKC) algorithms usually learn an optimal kernel from a group of pre-specified base kernels to improve the clustering performance. However, we observe that existing MKC algorithms do not well handle the situation that kernels are corrupted with noise and outliers.
Teng Li 0010 +4 more
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Communications of the ACM, 2018
Choosing between programming in the kernel or in user space.
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Choosing between programming in the kernel or in user space.
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