6 citations · 13 across the 9 of their papers we have counts for
5 papers · 1 filter
PageRank Bandits for Link Prediction
Yikun Ban, Jiaru Zou, Zihao Li +5
Link prediction is a critical problem in graph learning with broad applications such as recommender systems and knowledge graph completion. Numerous research efforts have been dire…
LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation
Xinrui He, Yikun Ban, Jiaru Zou +3
Missing data imputation is a critical challenge in various domains, such as healthcare and finance, where data completeness is vital for accurate analysis. Large language models (L…
Meta Clustering of Neural Bandits
Yikun Ban, Yunzhe Qi, Tianxin Wei +2
The contextual bandit has been identified as a powerful framework to formulate the recommendation process as a sequential decision-making process, where each item is regarded as an…
Neural Active Learning Beyond Bandits
Yikun Ban, Ishika Agarwal, Ziwei Wu +4
We study both stream-based and pool-based active learning with neural network approximations. A recent line of works proposed bandit-based approaches that transformed active learni…
Contextual Bandits with Online Neural Regression
Rohan Deb, Yikun Ban, Shiliang Zuo +2
Recent works have shown a reduction from contextual bandits to online regression under a realizability assumption [Foster and Rakhlin, 2020, Foster and Krishnamurthy, 2021]. In thi…