Thanks for your great work on this project — your input here would be really appreciated when you have a moment! It seems that Triton kernel example does not return sparsity, like CUDA kernel does ...
1 Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States 2 Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, United States Kernel Canonical ...
Abstract: The principal component analysis (PCA) is one of the most commonly used feature extraction methods in face recognition, but the traditional PCA method can't deal with the non-linear problem ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Previous research has proven the efficiency of PCA in ...
ABSTRACT: The speckle noise is considered one of the main causes of degradation in ultrasound image quality. Many despeckling filters have been proposed, which are always making a trade-off between ...
I am currently trying to create a kernel.pca with a meta-kernel object (from combine.kernels()) using the latest version of mixKernel. I am having some issue with ...
ABSTRACT: As an effective way in finding the underlying parameters of a high-dimension space, manifold learning is popular in nonlinear dimensionality reduction which makes high-dimensional data ...
Abstract: Though kernel methods have been widely used for feature extraction, it suffers from the problem that its feature extraction efficiency is in inverse proportion to the size of the training ...
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