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Locally Convex Sparse Learning over Networks
Our expectation is that local estimates in each node improve fast and converge, resulting in a limited demand for communication of estimates between nodes and reducing the processing time.
Estimate Exchange over Network is Good for Distributed Hard Thresholding Pursuit
The algorithm is iterative and exchanges intermediate estimates of a sparse signal over a network.
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