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- research-articleNovember 2018
Fast Network Simulation Through Approximation or: How Blind Men Can Describe Elephants
HotNets '18: Proceedings of the 17th ACM Workshop on Hot Topics in NetworksPages 141–147https://doi.org/10.1145/3286062.3286083Network researchers today are unable to test their new ideas at scale before deployment due to the prohibitive costs of custom testbeds and the slow speed of large-scale network simulators. Data center simulation is particularly slow because of the ...
A General and Efficient Querying Method for Learning to Hash
SIGMOD '18: Proceedings of the 2018 International Conference on Management of DataPages 1333–1347https://doi.org/10.1145/3183713.3183750As an effective solution to the approximate nearest neighbors (ANN) search problem, learning to hash (L2H) is able to learn similarity-preserving hash functions tailored for a given dataset. However, existing L2H research mainly focuses on improving ...
