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Jihyeon Lee

5 accepted papers

2023

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play

ICLR 2023poster

Standard empirical risk minimization (ERM) training can produce deep neural network (DNN) models that are accurate on average but under-perform in under-represented population subgroups, especially when there are imbalanced group distributions in the long-tailed training data. Therefore, approaches…

Cited by 2SourcePDFScholar
2021

Learning Debiased Representation via Disentangled Feature Augmentation

NeurIPS 2021oral

Image classification models tend to make decisions based on peripheral attributes of data items that have strong correlation with a target variable (i.e., dataset bias). These biased models suffer from the poor generalization capability when evaluated on unbiased datasets. Existing approaches for de…

Cited by 170SourcePDFScholar
2021

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery

AAAI 2021technical

Major decisions from governments and other large organizations rely on measurements of the populace's well-being, but making such measurements at a broad scale is expensive and thus infrequent in much of the developing world. We propose an inexpensive, scalable, and interpretable approach to predict…

2021

SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning

NeurIPS 2021poster

Progress toward the United Nations Sustainable Development Goals (SDGs) has been hindered by a lack of data on key environmental and socioeconomic indicators, which historically have come from ground surveys with sparse temporal and spatial coverage. Recent advances in machine learning have made it…

Cited by 74SourcecodeScholar