8 citations · 8 across the 5 of their papers we have counts for
3 papers · 1 filter
Efficient Tuning-Free -Regression of Nonnegative Compressible Signals
Hendrik Bernd Petersen, Bubacarr Bah, Peter Jung
In compressed sensing the goal is to recover a signal from as few as possible noisy, linear measurements. The general assumption is that the signal has only a few non-zero entries.…
On the construction of sparse matrices from expander graphs
Bubacarr Bah, Jared Tanner
We revisit the asymptotic analysis of probabilistic construction of adjacency matrices of expander graphs proposed in [4]. With better bounds we derived a new reduced sample comple…
Convex block-sparse linear regression with expanders -- provably
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad +3
Sparse matrices are favorable objects in machine learning and optimization. When such matrices are used, in place of dense ones, the overall complexity requirements in optimization…