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Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. Tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor...
In order to separate the chromatogram peaks and spectra from the High Performance Liquid Chromatography with Diode Array Detector (HPLC-DAD) data set, a separation model of Generalized Reference Curve Measurement and its solution by multitarget Bare Bones Particle Swarm Optimization (GRCMmBBPSO) is proposed in this paper. Firstly, parameters are constructed which will generate Reference Curves (RCs)...
In order to separate a 3D chromatography, which is generated from High Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD), into chromatograms and spectra, we proposed a model called parallel Independent Component Analysis constrained by Reference Curve (pICARC), which transforms the separation problem to a multi-parameter optimization issue. Then, A new algorithm named multi-areas Genetic...
Image super-resolution means forming high-resolution images from low-resolution images. In this paper, we develop a new approach based on the deep Restricted Boltzmann Machines (RBM) for image super-resolution. The RBM architecture has ability of learning a set of visual patterns, called dictionary elements from a set of training images. The learned dictionary will be then used to synthesize high...
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