Tree Search Network for Sparse Regression

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So OMP solvers are also being DNN-ized.

Tree Search Network for Sparse Regression by Kyung-Su Kim, Sae-Young Chung

We consider the classical sparse regression problem of recovering a sparse signal x0 given a measurement vector y=Φx0+w. We propose a tree search algorithm driven by the deep neural network for sparse regression (TSN). TSN improves the signal reconstruction performance of the deep neural network designed for sparse regression by performing a tree search with pruning. It is observed in both noiseless and noisy cases, TSN recovers synthetic and real signals with lower complexity than a conventional tree search and is superior to existing algorithms by a large margin for various types of the sensing matrix Φ, widely used in sparse regression.

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