Active Learning of Multiple Source Multiple Destination Topologies
@article{Sattari2013ActiveLO, title={Active Learning of Multiple Source Multiple Destination Topologies}, author={Pegah Sattari and Maciej Kurant and Anima Anandkumar and Athina Markopoulou and Michael G. Rabbat}, journal={IEEE Transactions on Signal Processing}, year={2013}, volume={62}, pages={1926-1937} }
We consider the problem of inferring the topology of a network with M sources and N receivers (an M-by- N network), by sending probes between the sources and receivers. Prior work has shown that this problem can be decomposed into two parts: first, infer smaller subnetwork components (1-by- N's or 2-by-2's) and then merge them to identify the M-by- N topology. We focus on the second part, which had previously received less attention in the literature. We assume that a 1-by- N topology is given…
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