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Dongyeon Woo

2 accepted papers

2024

Sample Selection via Contrastive Fragmentation for Noisy Label Regression

NeurIPS 2024poster

As with many other problems, real-world regression is plagued by the presence of noisy labels, an inevitable issue that demands our attention. Fortunately, much real-world data often exhibits an intrinsic property of continuously ordered correlations between labels and features, where data points w…

2021

Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration

ICLR 2021poster

We propose a novel information bottleneck (IB) method named Drop-Bottleneck, which discretely drops features that are irrelevant to the target variable. Drop-Bottleneck not only enjoys a simple and tractable compression objective but also additionally provides a deterministic compressed representati…