Selective Labeling via Error Bound Minimization

  title={Selective Labeling via Error Bound Minimization},
  author={Quanquan Gu and Tong Zhang and Chris H. Q. Ding and Jiawei Han},
In many practical machine learning problems, the acquisition of labeled data is often expensive and/or time consuming. This motivates us to study a problem as follows: given a label budget, how to select data points to label such that the learning performance is optimized. We propose a selective labeling method by analyzing the out-of-sample error of Laplacian regularized Least Squares (LapRLS). In particular, we derive a deterministic out-of-sample error bound for LapRLS trained on subsampled… CONTINUE READING


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