Gita Babazadeh Eslamlou — accepted AI-conference papers

2017

Smooth graph signal recovery via efficient Laplacian solvers

Gita Babazadeh Eslamlou, Alexander Jung, Norbert Goertz

ICASSP 2017accepted

We consider the problem of recovering a smooth graph signal from noisy samples observed at a small number of nodes. The signal recovery is formulated as a convex optimization problem using Tikhonov regularization based on the graph Laplacian quadratic form. The optimality conditions for this optimiz…

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2016

Graph signal recovery from incomplete and noisy information using approximate message passing

Gita Babazadeh Eslamlou, Alexander Jung, Norbert Goertz, Mehdi Fereydooni

ICASSP 2016accepted

We consider the problem of recovering a graph signal from noisy and incomplete information. In particular, we propose an approximate message passing based iterative method for graph signal recovery. The recovery of the graph signal is based on noisy signal values at a small number of randomly select…

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