Search Results for author: Yoon-Yeong Kim

Found 4 papers, 1 papers with code

Unknown Domain Inconsistency Minimization for Domain Generalization

no code implementations12 Mar 2024 Seungjae Shin, HeeSun Bae, Byeonghu Na, Yoon-Yeong Kim, Il-Chul Moon

In particular, by aligning the loss landscape acquired in the source domain to the loss landscape of perturbed domains, we expect to achieve generalization grounded on these flat minima for the unknown domains.

Domain Generalization

SAAL: Sharpness-Aware Active Learning

1 code implementation Proceedings of the 40th International Conference on Machine Learning 2023 Yoon-Yeong Kim, Youngjae Cho, JoonHo Jang, Byeonghu Na, Yeongmin Kim, Kyungwoo Song, Wanmo Kang, Il-Chul Moon

Specifically, our proposed method, Sharpness-Aware Active Learning (SAAL), constructs its acquisition function by selecting unlabeled instances whose perturbed loss becomes maximum.

Active Learning Image Classification +3

LADA: Look-Ahead Data Acquisition via Augmentation for Active Learning

no code implementations NeurIPS 2021 Yoon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-Chul Moon

Active learning effectively collects data instances for training deep learning models when the labeled dataset is limited and the annotation cost is high.

Active Learning Data Augmentation +1

Sequential Recommendation with Relation-Aware Kernelized Self-Attention

no code implementations15 Nov 2019 Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, Il-Chul Moon

This work merges the self-attention of the Transformer and the sequential recommendation by adding a probabilistic model of the recommendation task specifics.

Relation Sequential Recommendation

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