23 citations · 47 across the 15 of their papers we have counts for
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stat.ML2017
Estimate Exchange over Network is Good for Distributed Hard Thresholding Pursuit
Ahmed Zaki, Partha P. Mitra, Lars K. Rasmussen +1
We investigate an existing distributed algorithm for learning sparse signals or data over networks. The algorithm is iterative and exchanges intermediate estimates of a sparse sign…
stat.ML2017
A Connectedness Constraint for Learning Sparse Graphs
Martin Sundin, Arun Venkitaraman, Magnus Jansson +1
Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing. In some cases, the graph…