6 papers
A Recommendation System Approach for Interference-Robust Sensor Subset Selection
Kaan Buyukkalayci, Kyle Pak, Merve Karakas +1
This paper develops a method for sensor-subset selection for tracking. Prior work showed that low-cost acoustic Received Signal Strength Indicator (RSSI) measurements can be used t…
Top-P Sensor Selection for Target Localization
Kaan Buyukkalayci, Kyle Pak, Merve Karakas +2
We study set-valued decision rules in which performance is defined by the inclusion of the top- hypotheses, rather than only the single best or true hypothesis. This criterion i…
Multi-ResNets for Subspace Preconditioning in Constrained Optimization
Merve Karakas, Christopher J. Williams, Emmanuel O. Balogun +3
We propose MResOpt, a staged residual neural network architecture for constrained optimization problems. Our architecture fits within predict-complete-correct pipelines and decompo…
Best-Arm Identification with Noisy Actuation
Merve Karakas, Osama Hanna, Lin F. Yang +1
In this paper, we consider a multi-armed bandit (MAB) instance and study how to identify the best arm when arm commands are conveyed from a central learner to a distributed agent o…
Enhancing Binary Search via Overlapping Partitions
Kaan Buyukkalayci, Merve Karakas, Xinlin Li +1
This paper considers the task of performing binary search under noisy decisions, focusing on the application of target area localization. In the presence of noise, the classical pa…
Does Feedback Help in Bandits with Arm Erasures?
Merve Karakas, Osama Hanna, Lin F. Yang +1
We study a distributed multi-armed bandit (MAB) problem over arm erasure channels, motivated by the increasing adoption of MAB algorithms over communication-constrained networks. I…