61 citations · 188 across the 20 of their papers we have counts for
24 papers
AHP: Learning to Negative Sample for Hyperedge Prediction
Hyunjin Hwang, Seungwoo Lee, Chanyoung Park +1
Hypergraphs (i.e., sets of hyperedges) naturally represent group relations (e.g., researchers co-authoring a paper and ingredients used together in a recipe), each of which corresp…
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications
Shinhwan Kang, Kyuhan Lee, Kijung Shin
Are users of an online social network interested equally in all connections in the network? If not, how can we obtain a summary of the network personalized to specific users? Can w…
Meta-Learning for Online Update of Recommender Systems
Minseok Kim, Hwanjun Song, Yooju Shin +3
Online recommender systems should be always aligned with users' current interest to accurately suggest items that each user would like. Since user interest usually evolves over tim…
Are Edge Weights in Summary Graphs Useful? -- A Comparative Study
Shinhwan Kang, Kyuhan Lee, Kijung Shin
Which one is better between two representative graph summarization models with and without edge weights? From web graphs to online social networks, large graphs are everywhere. Gra…
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang +3
Deep learning has been successfully applied to precipitation nowcasting. In this work, we propose a pre-training scheme and a new loss function for improving deep-learning-based no…
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting
Geon Lee, Kijung Shin
Group interactions arise in our daily lives (email communications, on-demand ride sharing, comment interactions on online communities, to name a few), and they together form hyperg…