Rethinking Curriculum Learning with Incremental Labels and Adaptive Compensation
Rethinking Curriculum Learning with Incremental Labels and Adaptive Compensation
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Like humans, deep networks have been shown to learn better when samples are organized and introduced in a meaningful order or curriculum. Conventional curriculum learning schemes introduce samples in their order of difficulty. This forces models to begin learning from a subset of the available data while adding the external overhead of evaluating t...
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Rethinking Curriculum Learning with Incremental Labels and Adaptive Compensation
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TN_cdi_proquest_journals_2338876393
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2338876393
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2331-8422