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Preventing Adversarial Use of Datasets through Fair Core-Set Construction
Published 24 Oct 2019 in cs.LG, cs.AI, and stat.ML | (1910.10871v1)
Abstract: We propose improving the privacy properties of a dataset by publishing only a strategically chosen "core-set" of the data containing a subset of the instances. The core-set allows strong performance on primary tasks, but forces poor performance on unwanted tasks. We give methods for both linear models and neural networks and demonstrate their efficacy on data.
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