Sparse Randomized Shortest Paths Routing with Tsallis Divergence Regularization

This work elaborates on the important problem of (1) designing optimal randomized routing policies for reaching a target node t from a source note s on a weighted directed graph G and (2) defining distance measures between nodes interpolating between the least cost (based on optimal movements) and t...

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Veröffentlicht in:	arXiv.org 2020-07
Hauptverfasser:	Leleux, Pierre, Courtain, Sylvain, Guex, Guillaume, Saerens, Marco
Format:	Artikel
Sprache:	eng
Schlagworte:	Clustering Computer Science - Learning Distance measurement Graph theory Random walk Randomization Regularization Shortest-path problems Statistics - Machine Learning Transition probabilities
Online-Zugang:	Volltext
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