Learn the distinctions between simple and stratified random sampling. Understand how researchers use these methods to accurately represent data populations.

Abstract: Random walk is widely applied to sample large-scale graphs due to its simplicity of implementation and solid theoretical foundations of bias analysis. However, its computational efficiency ...

Abstract: Active learning has been widely used because it can automatically select the unlabeled samples with the largest amount of information for manual labeling. Therefore, it could solve the ...