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2020 – today
- 2025
[j26]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, Kijung Shin:
Compact lossy compression of tensors via neural tensor-train decomposition. Knowl. Inf. Syst. 67(2): 1169-1211 (2025)- [j25]Jihoon Ko
, Shinhwan Kang, Taehyung Kwon, Heechan Moon, Kijung Shin:
BeGin: Extensive Benchmark Scenarios and an Easy-to-use Framework for Graph Continual Learning. ACM Trans. Intell. Syst. Technol. 16(1): 19:1-19:22 (2025) - [j24]Hyunju Kim, Heechan Moon, Fanchen Bu, Jihoon Ko, Kijung Shin:
Estimating simplet counts via sampling. VLDB J. 34(2): 15 (2025) - [c86]Hyunjin Choo, Minho Eom, Gyuri Kim, Young-Gyu Yoon, Kijung Shin:
RASP: Robust Mining of Frequent Temporal Sequential Patterns under Temporal Variations. EDBT 2025: 233-245 - [c85]Euiwoong Lee, Kijung Shin:
Facility Location on High-Dimensional Euclidean Spaces. ITCS 2025: 70:1-70:21 - [i69]Hyeonsoo Jo, Hyunjin Hwang, Fanchen Bu, Soo Yong Lee, Chanyoung Park, Kijung Shin:
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications. CoRR abs/2501.05015 (2025) - [i68]Euiwoong Lee, Kijung Shin:
Facility Location on High-dimensional Euclidean Spaces. CoRR abs/2501.18105 (2025) - [i67]Junghun Lee, Hyunju Kim, Fanchen Bu, Jihoon Ko, Kijung Shin:
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation. CoRR abs/2502.01031 (2025) - [i66]Geon Lee, Wenchao Yu, Kijung Shin, Wei Cheng, Haifeng Chen:
TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents. CoRR abs/2502.11418 (2025) - 2024
- [j23]Jaewan Chun, Geon Lee, Kijung Shin, Jinhong Jung:
Random walk with restart on hypergraphs: fast computation and an application to anomaly detection. Data Min. Knowl. Discov. 38(3): 1222-1257 (2024) - [j22]Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin:
Representative and Back-In-Time Sampling from Real-world Hypergraphs. ACM Trans. Knowl. Discov. Data 18(6): 156:1-156:48 (2024) - [j21]Geon Lee, Seokbum Yoon, Jihoon Ko, Hyunju Kim, Kijung Shin:
Hypergraph motifs and their extensions beyond binary. VLDB J. 33(3): 625-665 (2024) - [c84]Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin, Sang-Wook Kim:
VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation. AAAI 2024: 8600-8607 - [c83]Dongjin Lee, Juho Lee, Kijung Shin:
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs. AAAI 2024: 13374-13382 - [c82]Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin:
Towards Better Utilization of Multiple Views for Bundle Recommendation. CIKM 2024: 3827-3831 - [c81]Geon Lee, Kyungho Kim, Kijung Shin:
Post-Training Embedding Enhancement for Long-Tail Recommendation. CIKM 2024: 3857-3861 - [c80]Dongyeong Hwang, Hyunju Kim, Sunwoo Kim, Kijung Shin:
FlowerFormer: Empowering Neural Architecture Encoding Using a Flow-Aware Graph Transformer. CVPR 2024: 6128-6137 - [c79]Ulugbek Ergashev, Geon Lee, Kijung Shin, Eduard C. Dragut, Weiyi Meng:
Resource2Box: Learning To Rank Resources in Distributed Search Using Box Embedding. ICDM 2024: 101-110 - [c78]Jihoon Ko, Taehyung Kwon, Jinhong Jung, Kijung Shin:
ELiCiT: Effective and Lightweight Lossy Compression of Tensors. ICDM 2024: 171-180 - [c77]Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin:
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs. ICLR 2024 - [c76]Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin:
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More. ICML 2024 - [c75]Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin:
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective. ICML 2024 - [c74]Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, Yuan Qi:
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs. ICML 2024 - [c73]Manh Tuan Do, Kijung Shin:
Unsupervised Alignment of Hypergraphs with Different Scales. KDD 2024: 609-620 - [c72]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, Kijung Shin:
Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors. KDD 2024: 1451-1462 - [c71]Jongha Lee, Sunwoo Kim, Kijung Shin:
SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning. KDD 2024: 1506-1517 - [c70]Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin:
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. KDD 2024: 6534-6544 - [c69]Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, Kijung Shin:
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy. NeurIPS 2024 - [c68]Geon Lee, Kyungho Kim, Kijung Shin:
Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation. RecSys 2024: 957-962 - [c67]Geon Lee, Soo Yong Lee, Kijung Shin:
VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation. WWW 2024: 594-605 - [c66]Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park:
Self-Guided Robust Graph Structure Refinement. WWW 2024: 697-708 - [i65]Geon Lee, Fanchen Bu, Tina Eliassi-Rad, Kijung Shin:
A Survey on Hypergraph Mining: Patterns, Tools, and Generators. CoRR abs/2401.08878 (2024) - [i64]Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin:
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective. CoRR abs/2402.04621 (2024) - [i63]Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park:
Self-Guided Robust Graph Structure Refinement. CoRR abs/2402.11837 (2024) - [i62]Jongha Lee, Sunwoo Kim, Kijung Shin:
SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning. CoRR abs/2402.11933 (2024) - [i61]Dongyeong Hwang, Hyunju Kim, Sunwoo Kim, Kijung Shin:
FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer. CoRR abs/2403.12821 (2024) - [i60]Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin:
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs. CoRR abs/2404.00638 (2024) - [i59]Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin:
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. CoRR abs/2404.01039 (2024) - [i58]Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin:
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More. CoRR abs/2405.08424 (2024) - [i57]Fanchen Bu, Ruochen Yang, Paul Bogdan, Kijung Shin:
Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms. CoRR abs/2405.16726 (2024) - [i56]Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, Yuan Qi:
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs. CoRR abs/2405.20652 (2024) - [i55]Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, Kijung Shin:
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy. CoRR abs/2410.20366 (2024) - 2023
- [j20]Fanchen Bu, Shinhwan Kang, Kijung Shin:
Interplay between topology and edge weights in real-world graphs: concepts, patterns, and an algorithm. Data Min. Knowl. Discov. 37(6): 2139-2191 (2023) - [j19]Sunwoo Kim, Dongjin Lee, Yul Kim, Jungho Park, Taeho Hwang, Kijung Shin:
Datasets, tasks, and training methods for large-scale hypergraph learning. Data Min. Knowl. Discov. 37(6): 2216-2254 (2023) - [j18]Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin:
Reciprocity in directed hypergraphs: measures, findings, and generators. Data Min. Knowl. Discov. 37(6): 2330-2388 (2023) - [j17]Fanchen Bu, Geon Lee, Kijung Shin:
Hypercore decomposition for non-fragile hyperedges: concepts, algorithms, observations, and applications. Data Min. Knowl. Discov. 37(6): 2389-2437 (2023) - [j16]Manh Tuan Do, Kijung Shin:
Improving the core resilience of real-world hypergraphs. Data Min. Knowl. Discov. 37(6): 2438-2493 (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) - [c65]Dongjin Lee, Kijung Shin:
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs. AAAI 2023: 8456-8464 - [c64]Hyeonsoo Jo, Fanchen Bu, Kijung Shin:
Robust Graph Clustering via Meta Weighting for Noisy Graphs. CIKM 2023: 1035-1044 - [c63]Soo Yong Lee, Juwon Kim, Kiwoong Park, Dong Kuk Ryu, Sang Heun Shim, Kijung Shin:
You're Not Alone in Battle: Combat Threat Analysis Using Attention Networks and a New Open Benchmark. CIKM 2023: 4033-4037 - [c62]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions. ICDM 2023: 229-238 - [c61]Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin:
Towards Deep Attention in Graph Neural Networks: Problems and Remedies. ICML 2023: 18774-18795 - [c60]Fanchen Bu, Kijung Shin:
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. KDD 2023: 117-129 - [c59]Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin:
Classification of Edge-dependent Labels of Nodes in Hypergraphs. KDD 2023: 298-309 - [c58]Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin:
How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. KDD 2023: 1132-1143 - [c57]Geon Lee, Jaemin Yoo, Kijung Shin:
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. KDD 2023: 5811-5812 - [c56]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 - [c55]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors. WWW 2023: 71-81 - [c54]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 - [c53]Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin:
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. WWW 2023: 317-327 - [c52]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 - [i54]Deukryeol Yoon, Dongjin Lee, Minyoung Choe, Kijung Shin:
Graphlets over Time: A New Lens for Temporal Network Analysis. CoRR abs/2301.00310 (2023) - [i53]Fanchen Bu, Geon Lee, Kijung Shin:
Hypercore Decomposition for Non-Fragile Hyperedges: Concepts, Algorithms, Observations, and Applications. CoRR abs/2301.08440 (2023) - [i52]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors. CoRR abs/2302.04570 (2023) - [i51]Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin:
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. CoRR abs/2302.05505 (2023) - [i50]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) - [i49]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) - [i48]Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin:
Towards Deep Attention in Graph Neural Networks: Problems and Remedies. CoRR abs/2306.02376 (2023) - [i47]Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin:
Classification of Edge-dependent Labels of Nodes in Hypergraphs. CoRR abs/2306.03032 (2023) - [i46]Fanchen Bu, Kijung Shin:
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. CoRR abs/2306.06368 (2023) - [i45]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) - [i44]Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin:
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions. CoRR abs/2309.10310 (2023) - [i43]Geon Lee, Seokbum Yoon, Jihoon Ko, Hyunju Kim, Kijung Shin:
Hypergraph Motifs and Their Extensions Beyond Binary. CoRR abs/2310.15668 (2023) - [i42]Hyeonsoo Jo, Fanchen Bu, Kijung Shin:
Robust Graph Clustering via Meta Weighting for Noisy Graphs. CoRR abs/2311.00322 (2023) - [i41]Heechan Moon, Hyunju Kim, Sunwoo Kim, Kijung Shin:
Four-set Hypergraphlets for Characterization of Directed Hypergraphs. CoRR abs/2311.14289 (2023) - [i40]Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin, Sang-Wook Kim:
VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation. CoRR abs/2312.12100 (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) - [c51]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 - [c50]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 - [c49]Geon Lee, Jaemin Yoo, Kijung Shin:
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. CIKM 2022: 5144-5147 - [c48]Kyuhan Lee, Jihoon Ko, Kijung Shin:
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs. ICDE 2022: 472-484 - [c47]Shinhwan Kang, Kyuhan Lee, Kijung Shin:
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications. ICDE 2022: 2319-2332 - [c46]Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin:
Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators. ICDM 2022: 1005-1010 - [c45]Geon Lee, Chanyoung Park, Kijung Shin:
Set2Box: Similarity Preserving Representation Learning for Sets. ICDM 2022: 1023-1028 - [c44]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 - [c43]Geon Lee, Minyoung Choe, Kijung Shin:
HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams. IJCAI 2022: 2129-2137 - [c42]Shinhwan Kang, Kyuhan Lee, Kijung Shin:
Are Edge Weights in Summary Graphs Useful? - A Comparative Study. PAKDD (1) 2022: 54-67 - [c41]Hyunjin Choo, Kijung Shin:
On the Persistence of Higher-Order Interactions in Real-World Hypergraphs. SDM 2022: 163-171 - [c40]Hyunjin Hwang, Seungwoo Lee, Chanyoung Park, Kijung Shin:
AHP: Learning to Negative Sample for Hyperedge Prediction. SIGIR 2022: 2237-2242 - [c39]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 - [c38]Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim:
Directed Network Embedding with Virtual Negative Edges. WSDM 2022: 1291-1299 - [c37]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) - [c36]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 - [c35]Taehyung Kwon, Inkyu Park, Dongjin Lee, Kijung Shin:
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams. ICDE 2021: 816-827 - [c34]Dongjin Lee, Kijung Shin:
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers. ICDE 2021: 840-851 - [c33]Geon Lee, Kijung Shin:
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting. ICDM 2021: 310-319 - [c32]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 - [c31]Aleksandra Gruca, Federico Serva, Llorenç Lliso, Pilar Rípodas, Xavier Calbet, Pedro Herruzo, Jirí Pihrt, Rudolf Raevskiy, Petr Simánek, Matej Choma, Yang Li, Haiyu Dong, Yury Belousov, Sergey Polezhaev, Brian Pulfer, Minseok Seo, Doyi Kim, Seungheon Shin, Eunbin Kim, Sewoong Ahn, Yeji Choi, Jinyoung Park, Minseok Son, Seungju Cho, Inyoung Lee, Changick Kim, Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin, Deukryeol Yoon, Seongha Eom, Kijung Shin, Se-Young Yun, Bertrand Le Saux, Michael K. Kopp, Sepp Hochreiter, David P. Kreil:
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. NeurIPS (Competition and Demos) 2021: 292-313 - [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]Kijung Shin:
WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams. CoRR abs/1709.03147 (2017) - 2016
- [j1]Jinhong Jung, Kijung Shin, Lee Sael, U Kang:
Random Walk with Restart on Large Graphs Using Block Elimination. ACM Trans. Database Syst. 41(2): 12:1-12:43 (2016) - [c7]Kijung Shin, Tina Eliassi-Rad, Christos Faloutsos:
CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms. ICDM 2016: 469-478 - [c6]Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos:
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage. KDD 2016: 895-904 - [c5]Kijung Shin, Bryan Hooi, Christos Faloutsos:
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees. ECML/PKDD (1) 2016: 264-280 - [c4]Hemank Lamba, Vaishnavh Nagarajan, Kijung Shin, Naji Shajarisales:
Incorporating Side Information in Tensor Completion. WWW (Companion Volume) 2016: 65-66 - 2015
- [c3]Kijung Shin, Jinhong Jung, Lee Sael, U Kang:
BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs. SIGMOD Conference 2015: 1571-1585 - 2014
- [c2]Dongyeop Kang, Woosang Lim, Kijung Shin, Lee Sael, U Kang:
Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression. CIKM 2014: 1269-1278 - [c1]Kijung Shin, U Kang:
Distributed Methods for High-Dimensional and Large-Scale Tensor Factorization. ICDM 2014: 989-994 - [i1]Kijung Shin, U Kang:
Distributed Methods for High-dimensional and Large-scale Tensor Factorization. CoRR abs/1410.5209 (2014)
Coauthor Index
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