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31
Representative and Back-In-Time Sampling from Real-world Hypergraphs
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin
ACM Transactions on Knowledge Discovery from Data
32
Robust Graph Clustering via Meta Weighting for N
33
Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression
Dongyeop Kang, Woosang Lim, Kijung Shin, Lee Sael, U Kang
ACM International Conference on Information and Knowledge Management, 2014
34
Distributed Methods for High-dimensional and Large-scale Tensor Factorization
Kijung Shin, U Kang
IEEE International Conference on Data Mining, 2014
35
BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs
Kijung Shin, Jinhong Jung, Lee Sael, U Kang
ACM SIGMOD International Conference on the Management of Data, 2015
36
CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms
Kijung Shin, Tina Eliassi-Rad, Christos Faloutsos
IEEE TKDE, 2016
37
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage
Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos
SIGKDD Conference on Knowledge Discovery and Data Mining, 2016
38
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees
Kijung Shin, Bryan Hooi, Christos Faloutsos
PKDD 2016, 2016
39
D-Cube: Dense-Block Detection in Terabyte-Scale Tensors
Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos
IJCAI 2017, 2017
40
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams
Kijung Shin
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2017, 2017
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