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cs.LG2025
A Class of Random-Kernel Network Models
James Tian
We introduce random-kernel networks, a multilayer extension of random feature models where depth is created by deterministic kernel composition and randomness enters only in the ou…
cs.LG2023
Conditional mean embeddings and optimal feature selection via positive definite kernels
Palle E. T. Jorgensen, Myung-Sin Song, James Tian
Motivated by applications, we consider here new operator theoretic approaches to Conditional mean embeddings (CME). Our present results combine a spectral analysis-based optimizati…
cs.LG2023
Operator theory, kernels, and Feedforward Neural Networks
Palle E. T. Jorgensen, Myung-Sin Song, James Tian
In this paper we show how specific families of positive definite kernels serve as powerful tools in analyses of iteration algorithms for multiple layer feedforward Neural Network m…