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Seo Taek Kong

2 accepted papers

2023

Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection

AAAI 2023technical

Out-of-distribution (OOD) detection can be used in deep learning-based applications to reject outlier samples from being unreliably classified by deep neural networks. Learning to classify between OOD and in-distribution samples is difficult because data comprising the former is extremely diverse. I…

2022

A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity

NeurIPS 2022accept

Deep learning (DL) algorithms rely on massive amounts of labeled data. Semi-supervised learning (SSL) and active learning (AL) aim to reduce this label complexity by leveraging unlabeled data or carefully acquiring labels, respectively. In this work, we primarily focus on designing an AL algorithm b…

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