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Estimating Fiedler value on large networks based on random walk observations

Alexandre Reiffers-Masson 1, 2 Thierry Chonavel 3, 4 Yezekael Hayel 5
2 Lab-STICC_MATHNET - Equipe Math & Net
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance : UMR6285
4 Lab-STICC_MATRIX - Equipe Models and AlgoriThms for pRocessIng and eXtracting information
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance : UMR6285
Abstract : In this paper, we describe an iterative scheme which is able to estimate the Fiedler value of a network when the topology is initially unknown. The only available information is the one obtained through a random walk process over the network. Our algorithm is based on the Rayleigh quotient optimization problem and the theory of stochastic approximation. We explain the different tools used to construct our algorithm and we describe our iterative scheme. Finally, we illustrate its performance through a numerical study. Index Terms Fiedler value, stochastic approximation, random walk based observations.
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Submitted on : Wednesday, October 21, 2020 - 6:26:59 PM
Last modification on : Monday, October 11, 2021 - 2:24:03 PM
Long-term archiving on: : Friday, January 22, 2021 - 7:01:39 PM

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Alexandre Reiffers-Masson, Thierry Chonavel, Yezekael Hayel. Estimating Fiedler value on large networks based on random walk observations. ICASSP 2021: IEEE International Conference on Acoustics, Speech and Signal Processing, Jun 2021, Toronto, Canada. ⟨10.1109/ICASSP39728.2021.9413713⟩. ⟨hal-02974433⟩

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