A Biased Estimator for MinMax Sampling and Distributed Aggregation

arXiv:2404.17690v1 Announce Type: new
Abstract: MinMax sampling is a technique for downsampling a real-valued vector which minimizes the maximum variance over all vector components. This approach is useful for reducing the amount of data that must be sent over a constrained network link (e.g. in the wide-area). MinMax can provide unbiased estimates of the vector elements, along with unbiased estimates of aggregates when vectors are combined from multiple locations. In this work, we propose a biased MinMax estimation scheme, B-MinMax, …

abstract aggregation arxiv components cs.dc cs.lg data distributed downsampling estimator maximum network sampling stat.ap type unbiased variance vector