【摘 要】
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Supervised leaing techniques construct predictive models by leaing from a large number of training examples,where each training example has a label indicating i
【机 构】
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National Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210023,China
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Supervised leaing techniques construct predictive models by leaing from a large number of training examples,where each training example has a label indicating its ground-truth output.Though current techniques have achieved great success,it is noteworthy that in many tasks it is difficult to get strong supervision information like fully ground-truth labels due to the high cost of the data-labeling process.Thus,it is desirable for machine-leaing techniques to work with weak supervision.This article reviews some research progress of weakly supervised leaing,focusing on three typical types of weak supervision:incomplete supervision,where only a subset of training data is given with labels;inexact supervision,where the training data are given with only coarse-grained labels;and inaccurate supervision,where the given labels are not always ground-truth.
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