Kernel ridge regression for generalized graph signal processing

In generalized graph signal processing (GGSP), a function (an element from a separable Hilbert space) is associated with each vertex. To perform non-linear filtering and regression under the GGSP framework, we formulate an operator-valued kernel ridge regression (KRR) filtering approach. Under a spe...

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Bibliographic Details
Main Authors: Jian, Xingchao, Tay, Wee Peng
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166434
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Institution: Nanyang Technological University
Language: English