Conference paper presented on the 27th European Signal Processing Conference (EUSIPCO) in which we propose an adaptive sampling method for the diffusion algorithm for adaptively learning from streaming graphs signals.

The solution allows a reduction in computational cost in steady state, while maintaining convergence rate and presenting a slightly better steady-state performance. We also present an analysis to give insights about proper choices for its adaptation parameters.

The PDF file can be obtained in this page.