A new gradient-discrepancy acquisition function derived from a generalization bound enables more effective pool-based active learning by selecting informative samples.
Learning representations by back- propagating errors
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Gradient-Discrepancy Acquisition for Pool-Based Active Learning
A new gradient-discrepancy acquisition function derived from a generalization bound enables more effective pool-based active learning by selecting informative samples.