Browse "RIMS Conference Papers" by Author Shin, Kijung
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| BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs Shin, Kijung; Jung, Jinhong; Lee, Sael; Kang, U, ACM SIGMOD International Conference on Management of Data (SIGMOD), pp.1571 - 1585, ACM Special Interest Group on Management of Data (SIGMOD), 2015-06-03 |
| DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams Shin, Kijung; Hooi, Bryan; Kim, Jisu; Faloutsos, Christos, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), 2017-08-16 |
| Discovering Progression Stages in Trillion-Scale Behavior Logs Shin, Kijung; Shafiei, Mahdi; Kim, Myunghwan; Jain, Aastha; Raghavan, Hema, World Wide Web Conference on World Wide Web (WWW), pp.1765 - 1774, ACM, 2018-04-26 |
| DPGS: Degree-Preserving Graph Summarization Zhou, Houquan; Liu, Shenghua; Lee, Kyuhan; Shin, Kijung; Shen, Huawei; Cheng, Xueqi, SIAM International Conference on Data Mining 2021, pp.280 - 288, Society for Industrial and Applied Mathematics, 2021-04-29 |
| Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data Han, Seungjae; Cho, Eun-Seo; Park, Inkyu; Shin, Kijung; Yoon, Young-Gyu, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.595 - 604, Springer International Publishing, 2021-09-28 |
| Evolution of Real-world Hypergraphs: Patterns and Models without Oracles Kook, Yunbum; Ko, Jihoon; Shin, Kijung, ICDM 2020: 20th IEEE International Conference on Data Mining, pp.272 - 281, IEEE Computer Society, 2020-11-19 |
| Fast and accurate anomaly detection in dynamic graphs with a two-pronged approach Yoon, Minji; Hooi, Bryan; Shin, Kijung; Faloutsos, Christos, 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019, pp.647 - 657, Association for Computing Machinery, 2019-08-06 |
| How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators Lee, Geon; Choe, Minyoung; Shin, Kijung, WWW '21: The Web Conference 2021, pp.3396 - 3407, ACM, 2021-04-19 |
| How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction Yoon, Se-eun; Song, Hyungseok; Shin, Kijung; Yi, Yung, The Web Conference 2020, WWW 2020, pp.2627 - 2633, Association for Computing Machinery, 2020-04-20 |
| MIDAS: MIcrocluster-based Detector of Anomalies in Edge Streams Bhatia, Siddharth; Hooi, Bryan; Yoon, Minji; Shin, Kijung; Faloutsos, Christos, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), pp.3243 - 3250, Association for the Advancement of Artificial Intelligence, 2020-02-10 |
| MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks Ko, Jihoon; Lee, Kyuhan; Shin, Kijung; Park, Noseong, 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp.204 - 211, IEEE Computer Society, 2020-12-09 |
| ONE-M: Modeling the Co-evolution of Opinions and Network Connections Nigam, Aastha; Shin, Kijung; Bahulkar, Ashwin; Hooi, Bryan; Hachen, David; Szymanski, Boleslaw K.; Faloutsos, Christos; et al, European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pp.122 - 140, Springer, 2018-09-13 |
| Robust factorization of real-world tensor streams with patterns, missing values, and outliers Lee, Dongjin; Shin, Kijung, 37th IEEE International Conference on Data Engineering, ICDE 2021, pp.840 - 851, IEEE Computer Society, 2021-04-19 |
| SliceNStitch: Continuous CP decomposition of sparse tensor streams Kwon, Taehyung; Park, Inkyu; Lee, Dongjin; Shin, Kijung, 37th IEEE International Conference on Data Engineering, ICDE 2021, pp.816 - 827, IEEE Computer Society, 2021-04-19 |
| SSumM: Sparse Summarization of Massive Graphs Lee, Kyuhan; Jo, Hyeonsoo; Ko, Jihoon; Lim, Sungsu; Shin, Kijung, 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2020, Association for Computing Machinery, 2020-08-24 |
| Structural Patterns and Generative Models of Real-world Hypergraphs Do, Manh Tuan; Yoon, Se-eun; Hooi, Bryan; Shin, Kijung, 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2020, Association for Computing Machinery, 2020-08-24 |
| SWeG: Lossless and Lossy Summarization of Web-Scale Graphs Shin, Kijung; Ghoting, Amol; Kim, Myunghwan; Raghavan, Hema, World Wide Web Conference on World Wide Web (WWW), pp.1679 - 1690, ACM, 2019-05-16 |
| TellTail: Fast Scoring and Detection of Dense Subgraphs Hooi, Bryan; Shin, Kijung; Lamba, Hemank; Faloutsos, Christos, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), pp.4150 - 4157, Association for the Advancement of Artificial Intelligence, 2020-02-10 |
| Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions Shin, Kijung; Kim, Jisu; Hooi, Bryan; Faloutsos, Christos, European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pp.141 - 157, Springer, 2018-09-13 |
| Tri-Fly: Distributed Estimation of Global and Local Triangle Counts in Graph Streams Shin, Kijung; Hammoud, Mohammad; Lee, Euiwoong; Oh, Jinoh; Faloutsos, Christos, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.651 - 663, Springer, 2018-06-05 |
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