Reviews: Faster Boosting with Smaller Memory

This paper uses "effective number of examples" and "weighted sampling", to reduce the used samples in each boosting round. The author provides theoretical analysis and explicit experiments to check the performance of the proposed method. But the abstract is harsh. It is unclear what's the core idea and intuition of the paper from the abstract. It simply names the three techniques. The experiments show that Sparrow reduces the memory needed to train boosting trees, and in some cases converges faster than other baselines trained in memory.