Exact(31)
spectrum intersection kernel.
The intersection kernel achieves the highest accuracy.
We use the histogram intersection kernel [17] for constructing the spectrum intersection kernel.
Next, we explain the spectrum intersection kernel for human motions.
Next, we explain the spectrum intersection kernel for music pieces.
Since the histogram intersection kernel is positive semi-definite [17], the spectrum intersection kernel can satisfy Mercer's theorem [15].
Similar(29)
It is interesting to compare the effect of characteristic kernels, which we are using in this paper, to histogram intersection kernels, which are not characteristic and are widely used in the computer vision literature [37 39] for classifying histogram-based data.
Our reported accuracy of 93.1%, obtained with characteristic kernels, is a very significant improvement with respect to the accuracy of 85.3% reported in [19], obtained using histogram intersection kernels in the same setting.
We consider Histogram Intersection (HI) kernel as a positive definite kernel.
For a free, discrete dynamical system, every ideal in the semicrossed product algebra is equal to an intersection of kernels of nest representations; a proper subset of all such kernels is a topological space homeomorphic to the space of all (discrete) finite arcs in the dynamical system, with the subarc topology.
It measures how far is the intersection between the kernel of the design matrix and the unit L1-ball from an L2-ball.
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