2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Collaborative Active Learning in Conditional Trust Environment
Zan-Kai Chong, Hiroyuki Ohsaki, Bryan Ng
In this paper, we investigate collaborative active learning, a paradigm in which multiple collaborators explore a new domain by leveraging their combined machine learning capabilit…
cs.LG2024★ 2 cited
Improving Uncertainty Sampling with Bell Curve Weight Function
Zan-Kai Chong, Hiroyuki Ohsaki, Bok-Min Goi
Typically, a supervised learning model is trained using passive learning by randomly selecting unlabelled instances to annotate. This approach is effective for learning a model, bu…
cs.LG2024
Improve Cost Efficiency of Active Learning over Noisy Dataset
Zan-Kai Chong, Hiroyuki Ohsaki, Bryan Ng
Active learning is a learning strategy whereby the machine learning algorithm actively identifies and labels data points to optimize its learning. This strategy is particularly eff…