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2026-03-05 16:08:22
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Learning with Limited Labeled Data, ICLR 2019 Toggle navigation Overview Sponsors Speakers Schedule Submission/dates FAQ Papers People LLD 2017 The 2nd Learning from Limited Labeled Data (LLD) Workshop Representation Learning for Weak Supervision and Beyond 6 May, 2019. New Orleans, USA Overview Modern representation learning techniques like deep neural networks have had a major impact on a wide range of tasks, achieving new state-of-the-art performances on benchmarks using little or no feature engineering. However, these gains are often difficult to translate into real-world settings because they usually require massive hand-labeled training sets. Collecting such training sets by hand is often infeasible due to the time and expense of labeling data; moreover, hand-labeled training sets are static and must be completely relabeled when real-world modeling goals change. Increasingly popular approaches for addressing this labeled data scarcity include usin...
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