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We show how specific families of positive definite kernels serve as powerful tools in analyses of iteration algorithms for multiple layer feedforward Neural Network models. Our focus is on particular kernels that adapt well to learning algorithms for data-sets/features which display intrinsic self-similarities at feedforward iterations of scaling.
Meeting ID: 856 9123 8129 Passcode: 712180
Host: 임미경     Korean English if it is requested     2026-03-13 13:31:15