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Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation
While for 2D images these networks are also computationally efficient, 3D convolutions have huge storage requirements and require long training time.
Analysis of regularized Nyström subsampling for regression functions of low smoothness
This paper studies a Nystr\"om type subsampling approach to large kernel learning methods in the misspecified case, where the target function is not assumed to belong to the reproducing kernel Hilbert space generated by the underlying kernel.
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