Sentence examples for kernel features from inspiring English sources

We demonstrate the discriminative power of heat kernel features in both synthetic and clinical preterm data.

Our approach is explored by the synthesis of three kernel features.

Multiple Empirical Kernel Learning (MEKL) explicitly maps samples into different empirical feature spaces in which the kernel features of the mapped samples can be directly provided.

Using cgroups allows exploiting Linux Kernel features that limit and allocate resources to VMs — such as CPU time, system memory, network bandwidth, or combinations of these resources [11].

We show that our heat kernel features are able to successfully predict motor function measured at two years of age (sensitivity, specificity, F-score, accuracy = 75.0, 82.5, 78.6, and 82.3%, respectively).

Using cgroups allows us to exploit Linux Kernel features which limit and allocate resources to VMs such as CPU time, system memory, network bandwidth, or combinations of these resources [11].

Figure 5 Deriving a new image in kernel feature space.

The third step was to design or to generate a new point in the kernel feature space using a kernel feature space algorithm.

Repeat until convergence: Sparse coding on the kernel feature space: (1) Perform the OMP algorithm.

This section reviews the decomposition based on KSVD algorithm and introduces our Kernel KSVD method in the kernel feature space.

The third step is to design or to generate a new point in the kernel feature space using a kernel feature space algorithm (e.g. the center of highly active compounds).