Conference Proceedings

Learning Based Distributed Tracking

Hao Wu, Junhao Gan, Rui Zhang

Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | ACM | Published : 2020


Inspired by the great success of machine learning in the past decade, people have been thinking about the possibility of improving the theoretical results by exploring data distribution. In this paper, we revisit a fundamental problem called Distributed Tracking (DT) under an assumption that the data follows a certain (known or unknown) distribution, and propose a number Data-dependent algorithms with improved theoretical bounds. Informally, in the DT problem, there is a coordinator and k players, where the coordinator holds a threshold N and each player has a counter. At each time stamp, at most one counter can be increased by one. The job of the coordinator is to capture the exact moment w..

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Awarded by Australian Research Council