740 citations · 2.2k across the 43 of their papers we have counts for
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Active Learning of Multiple Source Multiple Destination Topologies
Pegah Sattari, Maciej Kurant, Animashree Anandkumar +2
We consider the problem of inferring the topology of a network with sources and receivers (hereafter referred to as an -by- network), by sending probes between the so…
Background Subtraction for Online Calibration of Baseline RSS in RF Sensing Networks
Andrea Edelstein, Michael Rabbat
Radio frequency (RF) sensing networks are a class of wireless sensor networks (WSNs) which use RF signals to accomplish tasks such as passive device-free localization and tracking.…
Real-Time Multi-path Tracking of Probabilistic Available Bandwidth
Frederic Thouin, Mark Coates, Michael Rabbat
Applications such as traffic engineering and network provisioning can greatly benefit from knowing, in real time, what is the largest input rate at which it is possible to transmit…
Large scale probabilistic available bandwidth estimation
Frederic Thouin, Mark Coates, Michael Rabbat
The common utilization-based definition of available bandwidth and many of the existing tools to estimate it suffer from several important weaknesses: i) most tools report a point…
Multi-path Probabilistic Available Bandwidth Estimation through Bayesian Active Learning
Frederic Thouin, Mark Coates, Michael Rabbat
Knowing the largest rate at which data can be sent on an end-to-end path such that the egress rate is equal to the ingress rate with high probability can be very practical when cho…