19 citations · 54 across the 25 of their papers we have counts for
6 papers · 1 filter
Shift-Invariant Feature Attribution in the Application of Wireless Electrocardiograms
Yalemzerf Getnet, Abiy Tasissa, Waltenegus Dargie
Assigning relevance scores to the input features of a machine learning model enables to measure the contributions of the features in achieving a correct outcome. It is regarded as…
Robust Node Localization for Rough and Extreme Deployment Environments
Abiy Tasissa, Waltenegus Dargie
Many applications have been identified which require the deployment of large-scale low-power wireless sensor networks. Some of the deployment environments, however, impose harsh op…
Alternating minimization algorithm with initialization analysis for r-local and k-sparse unlabeled sensing
Ahmed Abbasi, Shuchin Aeron, Abiy Tasissa
Unlabeled sensing is a linear inverse problem with permuted measurements. We propose an alternating minimization (AltMin) algorithm with a suitable initialization for two widely co…
r-local sensing: Improved algorithm and applications
Ahmed Ali Abbasi, Abiy Tasissa, Shuchin Aeron
The unlabeled sensing problem is to solve a noisy linear system of equations under unknown permutation of the measurements. We study a particular case of the problem where the perm…
Weighed l1 on the simplex: Compressive sensing meets locality
Abiy Tasissa, Pranay Tankala, Demba Ba
Sparse manifold learning algorithms combine techniques in manifold learning and sparse optimization to learn features that could be utilized for downstream tasks. The standard sett…
R-local unlabeled sensing: A novel graph matching approach for multiview unlabeled sensing under local permutations
Ahmed Abbasi, Abiy Tasissa, Shuchin Aeron
Unlabeled sensing is a linear inverse problem where the measurements are scrambled under an unknown permutation leading to loss of correspondence between the measurements and the r…