Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares

NeurIPS 2016 Rong Zhu

In modern data analysis, random sampling is an efficient and widely-used strategy to overcome the computational difficulties brought by large sample size. In previous studies, researchers conducted random sampling which is according to the input data but independent on the response variable, however the response variable may also be informative for sampling... (read more)

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