Search Results for author: Kyeongryeol Go

Found 3 papers, 3 papers with code

Transferable Candidate Proposal with Bounded Uncertainty

1 code implementation7 Dec 2023 Kyeongryeol Go, Kye-Hyeon Kim

To tackle this issue, we introduce a new experimental design, coined as Candidate Proposal, to find transferable data candidates from which active learning algorithms choose the informative subset.

Active Learning Experimental Design +2

Meta-learning Amidst Heterogeneity and Ambiguity

1 code implementation5 Jul 2021 Kyeongryeol Go, Seyoung Yun

Meta-learning aims to learn a model that can handle multiple tasks generated from an unknown but shared distribution.

Meta-Learning regression

Cannot find the paper you are looking for? You can Submit a new open access paper.