Near-Optimal Herding

@inproceedings{Harvey2014NearOptimalH,
  title={Near-Optimal Herding},
  author={Nick Harvey and Samira Samadi},
  booktitle={COLT},
  year={2014}
}
Herding is an algorithm of recent interest in the machine learning community, motivated by inference in Markov random fields. It solves the following sampling problem: given a set X ⊂ R with mean μ, construct an infinite sequence of points from X such that, for every t ≥ 1, the mean of the first t points in that sequence lies within Euclidean distance O(1/t) of μ. The classic Perceptron boundedness theorem implies that such a result actually holds for a wide class of algorithms, although the… CONTINUE READING