Blar i NTNU Open på forfatter "Martins, Wallace"
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Adaptive Graph Filters in Reproducing Kernel Hilbert Spaces: Design and Performance Analysis
Elias, Vitor; Gogineni, Vinay Chakravarthi; Martins, Wallace; Werner, Stefan (Peer reviewed; Journal article, 2021)This paper develops adaptive graph filters that operate in reproducing kernel Hilbert spaces. We consider both centralized and fully distributed implementations. We first define nonlinear graph filters that operate on ... -
Graph diffusion kernel LMS using random Fourier features
Gogineni, Vinay Chakravarthi; Elias, Vitor; Martins, Wallace; Werner, Stefan (Chapter, 2021)This work introduces kernel adaptive graph filters that operate in the reproducing kernel Hilbert space. We propose a centralized graph kernel least mean squares (GKLMS) approach for identifying the nonlinear graph filters. ... -
Kernel regression on graphs in random Fourier features space
Elias, Vitor; Gogineni, Vinay Chakravarthi; Martins, Wallace; Werner, Stefan (Chapter, 2021)This work proposes an efficient batch-based implementation for kernel regression on graphs (KRG) using random Fourier features (RFF) and a low-complexity online implementation. Kernel regression has proven to be an efficient ... -
Kernel Regression over Graphs using Random Fourier Features
Meireles Elias, Vitor Rosa; Gogineni, Vinay Chakravarthi; Martins, Wallace; Werner, Stefan (Peer reviewed; Journal article, 2022)This paper proposes efficient batch-based and online strategies for kernel regression over graphs (KRG). The proposed algorithms do not require the input signal to be a graph signal, whereas the target signal is defined ...