4 accepted papers
Vector approximate message passing is studied where vectorvalued diagonalization instead of a uniform one is employed. Thereby,individualvariancesare tracked within the algorithm instead of an average one. Straightforward application based on the expectation-consistent approximate inference framewor…
The standard Approximate Message Passing (AMP) algorithm efficiently recovers a sparse signal from a small number of noisy linear measurements. It requires the measurement matrix to be zero-mean, however. Even small deviations from this requirement cause it to diverge. In this paper, we show how mea…
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…
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…