3 citations · 4 across the 7 of their papers we have counts for
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cs.LG2023
Transferable Candidate Proposal with Bounded Uncertainty
Kyeongryeol Go, Kye-Hyeon Kim
From an empirical perspective, the subset chosen through active learning cannot guarantee an advantage over random sampling when transferred to another model. While it underscores…
cs.LG2022★ 3 cited
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Mingyu Kim, Kyeongryeol Go, Se-Young Yun
Neural processes (NPs) aim to stochastically complete unseen data points based on a given context dataset. NPs essentially leverage a given dataset as a context representation to d…
cs.LG2021★ 1 cited
Meta-learning Amidst Heterogeneity and Ambiguity
Kyeongryeol Go, Seyoung Yun
Meta-learning aims to learn a model that can handle multiple tasks generated from an unknown but shared distribution. However, typical meta-learning algorithms have assumed the tas…