Abstract-- In this paper, we introduce the class of semiseparable kernel functions for use in constructing Lyapunov functions for distributed-parameter systems such as delaydiffere...
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
Primary visual cortex (V1) contains overlaid feature maps for orientation (OR), motion direction selectivity (DR), and ocular dominance (OD). Neurons in these maps are connected l...