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2020 – today
- 2023
[j15]Geon Lee, Kijung Shin
:
Temporal hypergraph motifs. Knowl. Inf. Syst. 65(4): 1549-1586 (2023)- [j14]Manh Tuan Do, Noseong Park, Kijung Shin:
Two-Stage Training of Graph Neural Networks for Graph Classification. Neural Process. Lett. 55(3): 2799-2823 (2023) - [c61]Dongjin Lee, Kijung Shin:
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs. AAAI 2023: 8456-8464 - [c60]Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin:
Towards Deep Attention in Graph Neural Networks: Problems and Remedies. ICML 2023: 18774-18795 - [c59]Fanchen Bu, Kijung Shin:
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. KDD 2023: 117-129 - [c58]Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin:
Classification of Edge-dependent Labels of Nodes in Hypergraphs. KDD 2023: 298-309 - [c57]Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin:
How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. KDD 2023: 1132-1143 - [c56]Geon Lee, Jaemin Yoo, Kijung Shin:
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. KDD 2023: 5811-5812 - [c55]Junmo Cho, Seungjae Han, Eun-Seo Cho, Kijung Shin, Young-Gyu Yoon:
Robust and Efficient Alignment of Calcium Imaging Data through Simultaneous Low Rank and Sparse Decomposition. WACV 2023: 1938-1947 - [c54]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors. WWW 2023: 71-81 - [c53]Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim:
Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding. WWW 2023: 231-239 - [c52]Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin:
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. WWW 2023: 317-327 - [c51]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [i50]Deukryeol Yoon, Dongjin Lee, Minyoung Choe, Kijung Shin:
Graphlets over Time: A New Lens for Temporal Network Analysis. CoRR abs/2301.00310 (2023) - [i49]Fanchen Bu, Geon Lee, Kijung Shin:
Hypercore Decomposition for Non-Fragile Hyperedges: Concepts, Algorithms, Observations, and Applications. CoRR abs/2301.08440 (2023) - [i48]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors. CoRR abs/2302.04570 (2023) - [i47]Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin:
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. CoRR abs/2302.05505 (2023) - [i46]Fanchen Bu, Shinhwan Kang, Kijung Shin:
Interplay between Topology and Edge Weights in Real-World Graphs: Concepts, Patterns, and an Algorithm. CoRR abs/2305.09083 (2023) - [i45]Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin:
How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. CoRR abs/2306.02358 (2023) - [i44]Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin:
Towards Deep Attention in Graph Neural Networks: Problems and Remedies. CoRR abs/2306.02376 (2023) - [i43]Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin:
Classification of Edge-dependent Labels of Nodes in Hypergraphs. CoRR abs/2306.03032 (2023) - [i42]Fanchen Bu, Kijung Shin:
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. CoRR abs/2306.06368 (2023) - [i41]Dongjin Lee, Juho Lee, Kijung Shin:
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs. CoRR abs/2308.10779 (2023) - [i40]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions. CoRR abs/2309.10310 (2023) - 2022
- [j13]Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Seok-Geun Oh, Seok-Woo Son, Kijung Shin:
Effective training strategies for deep-learning-based precipitation nowcasting and estimation. Comput. Geosci. 161: 105072 (2022) - [j12]Jihoon Ko, Yunbum Kook, Kijung Shin:
Growth patterns and models of real-world hypergraphs. Knowl. Inf. Syst. 64(11): 2883-2920 (2022) - [j11]Siddharth Bhatia, Rui Liu, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
Real-Time Anomaly Detection in Edge Streams. ACM Trans. Knowl. Discov. Data 16(4): 75:1-75:22 (2022) - [c50]Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee:
Meta-Learning for Online Update of Recommender Systems. AAAI 2022: 4065-4074 - [c49]Taeri Kim, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim:
MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation. CIKM 2022: 993-1002 - [c48]Geon Lee, Jaemin Yoo, Kijung Shin:
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. CIKM 2022: 5144-5147 - [c47]Kyuhan Lee, Jihoon Ko, Kijung Shin:
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs. ICDE 2022: 472-484 - [c46]Shinhwan Kang, Kyuhan Lee, Kijung Shin:
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications. ICDE 2022: 2319-2332 - [c45]Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin:
Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators. ICDM 2022: 1005-1010 - [c44]Geon Lee, Chanyoung Park, Kijung Shin:
Set2Box: Similarity Preserving Representation Learning for Sets. ICDM 2022: 1023-1028 - [c43]Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Kijung Shin:
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data. ICDM (Workshops) 2022: 1063-1070 - [c42]Geon Lee, Minyoung Choe, Kijung Shin:
HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams. IJCAI 2022: 2129-2137 - [c41]Shinhwan Kang, Kyuhan Lee, Kijung Shin:
Are Edge Weights in Summary Graphs Useful? - A Comparative Study. PAKDD (1) 2022: 54-67 - [c40]Hyunjin Choo, Kijung Shin:
On the Persistence of Higher-Order Interactions in Real-World Hypergraphs. SDM 2022: 163-171 - [c39]Hyunjin Hwang, Seungwoo Lee, Chanyoung Park, Kijung Shin:
AHP: Learning to Negative Sample for Hyperedge Prediction. SIGIR 2022: 2237-2242 - [c38]Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin:
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs. WSDM 2022: 908-916 - [c37]Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim:
Directed Network Embedding with Virtual Negative Edges. WSDM 2022: 1291-1299 - [c36]Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin:
MiDaS: Representative Sampling from Real-world Hypergraphs. WWW 2022: 1080-1092 - [i39]Hyunjin Choo, Kijung Shin:
On the Persistence of Higher-Order Interactions in Real-World Hypergraphs. CoRR abs/2201.00972 (2022) - [i38]Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin:
MiDaS: Representative Sampling from Real-world Hypergraphs. CoRR abs/2202.01587 (2022) - [i37]Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Seok-Geun Oh, Seok-Woo Son, Kijung Shin:
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation. CoRR abs/2202.10555 (2022) - [i36]Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee:
Meta-Learning for Online Update of Recommender Systems. CoRR abs/2203.10354 (2022) - [i35]Shinhwan Kang, Kyuhan Lee, Kijung Shin:
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications. CoRR abs/2203.14755 (2022) - [i34]Shinhwan Kang, Kyuhan Lee, Kijung Shin:
Are Edge Weights in Summary Graphs Useful? - A Comparative Study. CoRR abs/2203.15212 (2022) - [i33]Hyunjin Hwang, Seungwoo Lee, Chanyoung Park, Kijung Shin:
AHP: Learning to Negative Sample for Hyperedge Prediction. CoRR abs/2204.06353 (2022) - [i32]Geon Lee, Minyoung Choe, Kijung Shin:
HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams. CoRR abs/2204.13822 (2022) - [i31]Dongjin Lee, Kijung Shin:
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs. CoRR abs/2206.04739 (2022) - [i30]Geon Lee, Chanyoung Park, Kijung Shin:
Set2Box: Similarity Preserving Representation Learning of Sets. CoRR abs/2210.03282 (2022) - [i29]Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin:
Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators. CoRR abs/2210.05328 (2022) - [i28]Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Kijung Shin:
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data. CoRR abs/2210.12853 (2022) - [i27]Jihoon Ko, Shinhwan Kang, Kijung Shin:
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning. CoRR abs/2211.14568 (2022) - [i26]Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin, Deukryeol Yoon, Seongha Eom, Kijung Shin, Se-Young Yun:
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition. CoRR abs/2212.02059 (2022) - 2021
- [j10]Kijung Shin, Euiwoong Lee, Jinoh Oh, Mohammad Hammoud, Christos Faloutsos:
CoCoS: Fast and Accurate Distributed Triangle Counting in Graph Streams. ACM Trans. Knowl. Discov. Data 15(3): 38:1-38:30 (2021) - [c35]Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee:
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation. AAAI 2021: 4164-4171 - [c34]Taehyung Kwon, Inkyu Park, Dongjin Lee, Kijung Shin:
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams. ICDE 2021: 816-827 - [c33]Dongjin Lee, Kijung Shin:
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers. ICDE 2021: 840-851 - [c32]Geon Lee, Kijung Shin:
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting. ICDM 2021: 310-319 - [c31]Seungjae Han, Eun-Seo Cho, Inkyu Park, Kijung Shin, Young-Gyu Yoon:
Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data. MICCAI (7) 2021: 595-604 - [c30]Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng:
DPGS: Degree-Preserving Graph Summarization. SDM 2021: 280-288 - [c29]Geon Lee, Minyoung Choe, Kijung Shin:
How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators. WWW 2021: 3396-3407 - [i25]Geon Lee, Minyoung Choe, Kijung Shin:
How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators. CoRR abs/2101.07480 (2021) - [i24]Dongjin Lee, Kijung Shin:
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers. CoRR abs/2102.08466 (2021) - [i23]Taehyung Kwon, Inkyu Park, Dongjin Lee, Kijung Shin:
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams. CoRR abs/2102.11517 (2021) - [i22]Jihoon Ko, Taehyung Kwon, Kijung Shin, Juho Lee:
Learning to Pool in Graph Neural Networks for Extrapolation. CoRR abs/2106.06210 (2021) - [i21]Geon Lee, Kijung Shin:
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting. CoRR abs/2109.08341 (2021) - [i20]Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin:
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs. CoRR abs/2110.14875 (2021) - [i19]Kyuhan Lee, Jihoon Ko, Kijung Shin:
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs. CoRR abs/2112.05374 (2021) - 2020
- [j9]Jiyuan Zhang, Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, Hwanjo Yu:
Fast and memory-efficient algorithms for high-order Tucker decomposition. Knowl. Inf. Syst. 62(7): 2765-2794 (2020) - [j8]Geon Lee, Jihoon Ko, Kijung Shin:
Hypergraph Motifs: Concepts, Algorithms, and Discoveries. Proc. VLDB Endow. 13(11): 2256-2269 (2020) - [j7]Kijung Shin, Sejoon Oh, Jisu Kim, Bryan Hooi, Christos Faloutsos:
Fast, Accurate and Provable Triangle Counting in Fully Dynamic Graph Streams. ACM Trans. Knowl. Discov. Data 14(2): 12:1-12:39 (2020) - [j6]Dongjin Lee, Kijung Shin, Christos Faloutsos:
Temporal locality-aware sampling for accurate triangle counting in real graph streams. VLDB J. 29(6): 1501-1525 (2020) - [c28]Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
Midas: Microcluster-Based Detector of Anomalies in Edge Streams. AAAI 2020: 3242-3249 - [c27]Bryan Hooi, Kijung Shin, Hemank Lamba, Christos Faloutsos:
TellTail: Fast Scoring and Detection of Dense Subgraphs. AAAI 2020: 4150-4157 - [c26]Jihoon Ko, Kyuhan Lee, Kijung Shin, Noseong Park:
MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks. ASONAM 2020: 204-211 - [c25]Yunbum Kook, Jihoon Ko, Kijung Shin:
Evolution of Real-world Hypergraphs: Patterns and Models without Oracles. ICDM 2020: 272-281 - [c24]Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin:
SSumM: Sparse Summarization of Massive Graphs. KDD 2020: 144-154 - [c23]Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin:
Structural Patterns and Generative Models of Real-world Hypergraphs. KDD 2020: 176-186 - [c22]Jihoon Ko, Yunbum Kook, Kijung Shin:
Incremental Lossless Graph Summarization. KDD 2020: 317-327 - [c21]Se-eun Yoon, HyungSeok Song, Kijung Shin, Yung Yi:
How Much and When Do We Need Higher-order Informationin Hypergraphs? A Case Study on Hyperedge Prediction. WWW 2020: 2627-2633 - [i18]Jihoon Ko, Kyuhan Lee, Kijung Shin, Noseong Park:
MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Social Networks. CoRR abs/2001.08853 (2020) - [i17]Se-eun Yoon, HyungSeok Song, Kijung Shin, Yung Yi:
How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction. CoRR abs/2001.11181 (2020) - [i16]Geon Lee, Jihoon Ko, Kijung Shin:
Hypergraph Motifs: Concepts, Algorithms, and Discoveries. CoRR abs/2003.01853 (2020) - [i15]Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin:
SSumM: Sparse Summarization of Massive Graphs. CoRR abs/2006.01060 (2020) - [i14]Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin:
Structural Patterns and Generative Models of Real-world Hypergraphs. CoRR abs/2006.07060 (2020) - [i13]Jihoon Ko, Yunbum Kook, Kijung Shin:
Incremental Lossless Graph Summarization. CoRR abs/2006.09935 (2020) - [i12]Yunbum Kook, Jihoon Ko, Kijung Shin:
Evolution of Real-world Hypergraphs: Patterns and Models without Oracles. CoRR abs/2008.12729 (2020) - [i11]Siddharth Bhatia, Rui Liu, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
Real-Time Streaming Anomaly Detection in Dynamic Graphs. CoRR abs/2009.08452 (2020) - [i10]Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng:
Summarizing graphs using the configuration model. CoRR abs/2010.09175 (2020) - [i9]Manh Tuan Do, Noseong Park, Kijung Shin:
Two-stage Training of Graph Neural Networks for Graph Classification. CoRR abs/2011.05097 (2020) - [i8]Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos:
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. CoRR abs/2011.13085 (2020)
2010 – 2019
- 2019
- [c20]Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos:
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. KDD 2019: 647-657 - [c19]Bryan Hooi, Kijung Shin, Shenghua Liu, Christos Faloutsos:
SMF: Drift-Aware Matrix Factorization with Seasonal Patterns. SDM 2019: 621-629 - [c18]Kijung Shin, Amol Ghoting, Myunghwan Kim, Hema Raghavan:
SWeG: Lossless and Lossy Summarization of Web-Scale Graphs. WWW 2019: 1679-1690 - [i7]Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams. CoRR abs/1911.04464 (2019) - 2018
- [j5]Kijung Shin, Tina Eliassi-Rad, Christos Faloutsos:
Patterns and anomalies in k-cores of real-world graphs with applications. Knowl. Inf. Syst. 54(3): 677-710 (2018) - [j4]Kijung Shin, Bryan Hooi, Christos Faloutsos:
Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining. ACM Trans. Knowl. Discov. Data 12(3): 28:1-28:30 (2018) - [c17]Kijung Shin, Mohammad Hammoud, Euiwoong Lee, Jinoh Oh, Christos Faloutsos:
Tri-Fly: Distributed Estimation of Global and Local Triangle Counts in Graph Streams. PAKDD (3) 2018: 651-663 - [c16]Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski, Christos Faloutsos, Nitesh V. Chawla:
ONE-M: Modeling the Co-evolution of Opinions and Network Connections. ECML/PKDD (2) 2018: 122-140 - [c15]Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos:
Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions. ECML/PKDD (2) 2018: 141-157 - [c14]Kijung Shin, Mahdi Shafiei, Myunghwan Kim, Aastha Jain, Hema Raghavan:
Discovering Progression Stages in Trillion-Scale Behavior Logs. WWW 2018: 1765-1774 - [i6]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
Out-of-Core and Distributed Algorithms for Dense Subtensor Mining. CoRR abs/1802.01065 (2018) - [i5]Kijung Shin, Euiwoong Lee, Jinoh Oh, Mohammad Hammoud, Christos Faloutsos:
DiSLR: Distributed Sampling with Limited Redundancy For Triangle Counting in Graph Streams. CoRR abs/1802.04249 (2018) - 2017
- [j3]Bryan Hooi, Kijung Shin, Hyun Ah Song, Alex Beutel, Neil Shah, Christos Faloutsos:
Graph-Based Fraud Detection in the Face of Camouflage. ACM Trans. Knowl. Discov. Data 11(4): 44:1-44:26 (2017) - [j2]Kijung Shin, Lee Sael, U Kang:
Fully Scalable Methods for Distributed Tensor Factorization. IEEE Trans. Knowl. Data Eng. 29(1): 100-113 (2017) - [c13]Kijung Shin:
WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams. ICDM 2017: 1087-1092 - [c12]Kijung Shin, Euiwoong Lee, Dhivya Eswaran, Ariel D. Procaccia:
Why You Should Charge Your Friends for Borrowing Your Stuff. IJCAI 2017: 395-401 - [c11]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams. KDD 2017: 1057-1066 - [c10]Hemank Lamba, Bryan Hooi, Kijung Shin, Christos Faloutsos, Jürgen Pfeffer:
zooRank: Ranking Suspicious Entities in Time-Evolving Tensors. ECML/PKDD (1) 2017: 68-84 - [c9]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
D-Cube: Dense-Block Detection in Terabyte-Scale Tensors. WSDM 2017: 681-689 - [c8]Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, Hwanjo Yu:
S-HOT: Scalable High-Order Tucker Decomposition. WSDM 2017: 761-770 - [i4]Kijung Shin, Euiwoong Lee, Dhivya Eswaran, Ariel D. Procaccia:
Why You Should Charge Your Friends for Borrowing Your Stuff. CoRR abs/1705.07343 (2017) - [i3]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams. CoRR abs/1706.03374 (2017) - [i2]