no code implementations • 11 Aug 2023 • Jun Hee Kim, Jaeman Son, Hyunsoo Kim, EunJo Lee
In this paper, we propose ARGEW (Augmentation of Random walks by Graph Edge Weights), a novel augmentation method for random walks that expands the corpus in such a way that nodes with larger edge weights end up with closer embeddings.
no code implementations • 5 Feb 2022 • Hazel Kim, Jaeman Son, Yo-Sub Han
Self-training provides an effective means of using an extremely small amount of labeled data to create pseudo-labels for unlabeled data.