70 citations · 467 across the 48 of their papers we have counts for
8 papers · 1 filter
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs
Kyuhan Lee, Jihoon Ko, Kijung Shin
Given a massive graph, how can we exploit its hierarchical structure for concisely but exactly summarizing the graph? By exploiting the structure, can we achieve better compression…
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs
Hyeonjeong Shin, Taehyung Kwon, Neil Shah +1
A variety of tasks on dynamic graphs, including anomaly detection, community detection, compression, and graph understanding, have been formulated as problems of identifying consti…
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…
Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data
Seungjae Han, Eun-Seo Cho, Inkyu Park +2
Calcium imaging is an essential tool to study the activity of neuronal populations. However, the high level of background fluorescence in images hinders the accurate identification…
Learning to Pool in Graph Neural Networks for Extrapolation
Jihoon Ko, Taehyung Kwon, Kijung Shin +1
Graph neural networks (GNNs) are one of the most popular approaches to using deep learning on graph-structured data, and they have shown state-of-the-art performances on a variety…
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams
Taehyung Kwon, Inkyu Park, Dongjin Lee +1
Consider traffic data (i.e., triplets in the form of source-destination-timestamp) that grow over time. Tensors (i.e., multi-dimensional arrays) with a time mode are widely used fo…
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers
Dongjin Lee, Kijung Shin
Consider multiple seasonal time series being collected in real-time, in the form of a tensor stream. Real-world tensor streams often include missing entries (e.g., due to network d…
How Do Hyperedges Overlap in Real-World Hypergraphs? -- Patterns, Measures, and Generators
Geon Lee, Minyoung Choe, Kijung Shin
Hypergraphs, a generalization of graphs, naturally represent groupwise relationships among multiple individuals or objects, which are common in many application areas, including we…