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CIF: Small: Resource-Constrained Distributed Multiple Testing with False Discovery Rate Co — NSF Award to University of Utah (UT,

Distributed intelligence with large amounts of local measurement data hinges on the design of devices that are capable of sensing, processing, and exchanging local information. Reliable decision-making in a collective manner is, however, a challenging task in resource-constrained scenarios, where devices are limited by

Award titleCIF: Small: Resource-Constrained Distributed Multiple Testing with False Discovery Rate Co
Award ID2420146
AwardeeUniversity of Utah
CitySALT LAKE CITY
StateUT
Amount obligated$199,991
Principal investigatorYu Xiang
ProgramComm & Information Foundations
Start date12/15/2024
AbstractDistributed intelligence with large amounts of local measurement data hinges on the design of devices that are capable of sensing, processing, and exchanging local information. Reliable decision-making in a collective manner is, however, a challenging task in resource-constrained scenarios, where devices are limited by communication costs and/or processing power. This project aims to develop a new framework for designing efficient decentralized algorithms such that the average proportion of wron
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