Sublinear Time Approximate Sum via Uniform Random Sampling
  We investigate the approximation for computing the sum $a_1+...+a_n$ with an input of a list of nonnegative elements $a_1,..., a_n$. If all elements are in the range $[0,1]$, there is a randomized algorithm that can compute an $(1+\epsilon)$-approximation for the sum problem in time ${O({n(\log\log n)\over\sum_{i=1}^n a_i})}$, where $\epsilon$ is a constant in $(0,1)$. Our randomized algorithm is based on the uniform random sampling, which selects one element with equal probability from the input list each time. We also prove a lower bound $\Omega({n\over \sum_{i=1}^n a_i})$, which almost matches the upper bound, for this problem. 
Bin Fu, Wenfeng Li, and Zhiyong Peng
cs.DS