Kijung Shin

236 papers A* 70A 20B 2Journal 125Unranked 19
YearRankTypeTitle / Venue / Authors
2026 J jnl
A comprehensive survey on multi-behavior recommender systems: extended taxonomy and recent advances.
Int. J. Data Sci. Anal.
Kyungho Kim, Sunwoo Kim, Geon Lee, Jinhong Jung, Kijung Shin
2026 J jnl
Effective Dataset Distillation for Spatio-Temporal Forecasting with Bi-dimensional Compression.
CoRR
Taehyung Kwon, Yeonje Choi, Yeongho Kim, Kijung Shin
2026 A* conf
Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption.
AAAI
Sunwoo Kim, Soo Yong Lee, Kyungho Kim, Hyunjin Hwang, Jaemin Yoo, Kijung Shin
2026 A* conf
Personalized Parameter-Efficient Fine-Tuning of Foundation Models for Multimodal Recommendation.
WWW
Sunwoo Kim, Hyunjin Hwang, Kijung Shin
2026 J jnl
Personalized Parameter-Efficient Fine-Tuning of Foundation Models for Multimodal Recommendation.
CoRR
Sunwoo Kim, Hyunjin Hwang, Kijung Shin
2026 A* conf
ReFuGe: Feature Generation for Prediction Tasks on Relational Databases with LLM Agents.
WWW
Kyungho Kim, Geon Lee, Juyeon Kim, Dongwon Choi, Shinhwan Kang, Kijung Shin
2026 J jnl
ReFuGe: Feature Generation for Prediction Tasks on Relational Databases with LLM Agents.
CoRR
Kyungho Kim, Geon Lee, Juyeon Kim, Dongwon Choi, Shinhwan Kang, Kijung Shin
2026 A conf
Sequential Data Augmentation for Generative Recommendation.
WSDM
Geon Lee, Bhuvesh Kumar, Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, Liam Collins
2025 — conf
'Hello, World!': Making GNNs Talk with LLMs.
EMNLP (Findings)
Sunwoo Kim, Soo Yong Lee, Jaemin Yoo, Kijung Shin
2025 J jnl
'Hello, World!': Making GNNs Talk with LLMs.
CoRR
Sunwoo Kim, Soo Yong Lee, Jaemin Yoo, Kijung Shin
2025 A conf
A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation.
CIKM
Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin
2025 J jnl
A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation.
CoRR
Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin
2025 J jnl
A Survey on Centrality and Importance Measures in Hypergraphs: Categorization and Empirical Insights.
CoRR
Jaewan Chun, Fanchen Bu, Yeongho Kim, Atsushi Miyauchi, Francesco Bonchi, Kijung Shin
2025 J jnl
A Survey on Hypergraph Mining: Patterns, Tools, and Generators.
ACM Comput. Surv.
Geon Lee, Fanchen Bu, Tina Eliassi-Rad, Kijung Shin
2025 A conf
A Tutorial on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide.
CIKM
Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
2025 A* conf
Attributed Hypergraph Generation with Realistic Interplay Between Structure and Attributes.
ICDM
Jaewan Chun, Seokbum Yoon, Minyoung Choe, Geon Lee, Kijung Shin
2025 J jnl
Attributed Hypergraph Generation with Realistic Interplay Between Structure and Attributes.
CoRR
Jaewan Chun, Seokbum Yoon, Minyoung Choe, Geon Lee, Kijung Shin
2025 J jnl
BeGin: Extensive Benchmark Scenarios and an Easy-to-use Framework for Graph Continual Learning.
ACM Trans. Intell. Syst. Technol.
Jihoon Ko, Shinhwan Kang, Taehyung Kwon, Heechan Moon, Kijung Shin
2025 A* conf
Beyond Neighbors: Distance-Generalized Graphlets for Enhanced Graph Characterization.
WWW
Yeongho Kim, Yuyeong Kim, Geon Lee, Kijung Shin
2025 J jnl
Compact lossy compression of tensors via neural tensor-train decomposition.
Knowl. Inf. Syst.
Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, Kijung Shin
2025 A* conf
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation.
AAAI
Junghun Lee, Hyunju Kim, Fanchen Bu, Jihoon Ko, Kijung Shin
2025 J jnl
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation.
CoRR
Junghun Lee, Hyunju Kim, Fanchen Bu, Jihoon Ko, Kijung Shin
2025 A* conf
Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms.
ICDM
Fanchen Bu, Ruochen Yang, Paul Bogdan, Kijung Shin
2025 J jnl
Effective and lightweight lossy compression of tensors: techniques and applications.
Knowl. Inf. Syst.
Jihoon Ko, Taehyung Kwon, Jinhong Jung, Kijung Shin
2025 J jnl
Emergence of psychopathological computations in large language models.
CoRR
Soo Yong Lee, Hyunjin Hwang, Taekwan Kim, Yuyeong Kim, Kyuri Park, Jaemin Yoo, Denny Borsboom, Kijung Shin
2025 J jnl
Estimating simplet counts via sampling.
VLDB J.
Hyunju Kim, Heechan Moon, Fanchen Bu, Jihoon Ko, Kijung Shin
2025 J jnl
Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop.
CoRR
Yushan Jiang, Wenchao Yu, Geon Lee, Dongjin Song, Kijung Shin, Wei Cheng, Yanchi Liu, Haifeng Chen
2025 J jnl
Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption.
CoRR
Sunwoo Kim, Soo Yong Lee, Kyungho Kim, Hyunjin Hwang, Jaemin Yoo, Kijung Shin
2025 J jnl
From Raw Features to Effective Embeddings: A Three-Stage Approach for Multimodal Recipe Recommendation.
CoRR
Jeeho Shin, Kyungho Kim, Kijung Shin
2025 J jnl
Gene expression inference based on graph neural networks using L1000 data.
Briefings Bioinform.
Tae Hyun Kim, Harim Kim, Hyunjin Hwang, Shinwhan Kang, Kijung Shin, Inwha Baek
2025 J jnl
Hybrid-Vector Retrieval for Visually Rich Documents: Combining Single-Vector Efficiency and Multi-Vector Accuracy.
CoRR
Juyeon Kim, Geon Lee, Dongwon Choi, Taeuk Kim, Kijung Shin
2025 A* conf
HyperSearch: Prediction of New Hyperedges Through Unconstrained yet Efficient Search.
ICDM
Hyunjin Choo, Fanchen Bu, Hyunjin Hwang, Young-Gyu Yoon, Kijung Shin
2025 J jnl
HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search.
CoRR
Hyunjin Choo, Fanchen Bu, Hyunjin Hwang, Young-Gyu Yoon, Kijung Shin
2025 A* conf
Identifying Group Anchors in Real-World Group Interactions Under Label Scarcity.
ICDM
Fanchen Bu, Geon Lee, Kijung Shin, Minyoung Choe
2025 J jnl
Identifying Group Anchors in Real-World Group Interactions Under Label Scarcity.
CoRR
Fanchen Bu, Geon Lee, Minyoung Choe, Kijung Shin
2025 J jnl
Inductive influence estimation and maximization over unseen social networks under two diffusion models.
Data Min. Knowl. Discov.
Jihoon Ko, Sojeong Kim, Kyuhan Lee, Shinhwan Kang, Dongyeong Hwang, Kijung Shin, Noseong Park
2025 J jnl
ItemRAG: Item-Based Retrieval-Augmented Generation for LLM-Based Recommendation.
CoRR
Sunwoo Kim, Geon Lee, Kyungho Kim, Jaemin Yoo, Kijung Shin
2025 A* conf
KGMEL: Knowledge Graph-Enhanced Multimodal Entity Linking.
SIGIR
Juyeon Kim, Geon Lee, Taeuk Kim, Kijung Shin
2025 J jnl
KGMEL: Knowledge Graph-Enhanced Multimodal Entity Linking.
CoRR
Juyeon Kim, Geon Lee, Taeuk Kim, Kijung Shin
2025 A* conf
Kronecker Generative Models for Power-Law Patterns in Real-World Hypergraphs.
WWW
Minyoung Choe, Jihoon Ko, Taehyung Kwon, Kijung Shin, Christos Faloutsos
2025 J jnl
Learning to Flow from Generative Pretext Tasks for Neural Architecture Encoding.
CoRR
Sunwoo Kim, Hyunjin Hwang, Kijung Shin
2025 A* conf
MARIOH: Multiplicity-Aware Hypergraph Reconstruction.
ICDE
Kyuhan Lee, Geon Lee, Kijung Shin
2025 J jnl
MARIOH: Multiplicity-Aware Hypergraph Reconstruction.
CoRR
Kyuhan Lee, Geon Lee, Kijung Shin
2025 A* conf
Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification.
ICML
Langzhang Liang, Fanchen Bu, Zixing Song, Zenglin Xu, Shirui Pan, Kijung Shin
2025 J jnl
Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification.
CoRR
Langzhang Liang, Fanchen Bu, Zixing Song, Zenglin Xu, Shirui Pan, Kijung Shin
2025 J jnl
Multi-Behavior Recommender Systems: A Survey.
CoRR
Kyungho Kim, Sunwoo Kim, Geon Lee, Jinhong Jung, Kijung Shin
2025 — conf
Multi-behavior Recommender Systems: A Survey.
PAKDD (4)
Kyungho Kim, Sunwoo Kim, Geon Lee, Jinhong Jung, Kijung Shin
2025 — conf
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications.
KDD (1)
Hyeonsoo Jo, Hyunjin Hwang, Fanchen Bu, Soo Yong Lee, Chanyoung Park, Kijung Shin
2025 J jnl
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications.
CoRR
Hyeonsoo Jo, Hyunjin Hwang, Fanchen Bu, Soo Yong Lee, Chanyoung Park, Kijung Shin
2025 J jnl
On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis.
CoRR
Fanchen Bu, Kijung Shin
2025 A ed.
Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025
CIKM
Meeyoung Cha, Chanyoung Park, Noseong Park, Carl Yang, Senjuti Basu Roy, Jessie Li, Jaap Kamps, Kijung Shin, Bryan Hooi, Lifang He
2025 J jnl
PyTorch-based Geometric Learning with Non-CUDA Processing Units: Experiences from Intel Gaudi-v2 HPUs.
CoRR
Fanchen Bu, Kijung Shin
2025 B conf
RASP: Robust Mining of Frequent Temporal Sequential Patterns under Temporal Variations.
EDBT
Hyunjin Choo, Minho Eom, Gyuri Kim, Young-Gyu Yoon, Kijung Shin
2025 J jnl
RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases.
CoRR
Dongwon Choi, Sunwoo Kim, Juyeon Kim, Kyungho Kim, Geon Lee, Shinhwan Kang, Myunghwan Kim, Kijung Shin
2025 — conf
RL4CO: An Extensive Reinforcement Learning for Combinatorial Optimization Benchmark.
KDD (2)
Federico Berto, Chuanbo Hua, Junyoung Park, Laurin Luttmann, Yining Ma, Fanchen Bu, Jiarui Wang, Haoran Ye, Minsu Kim, Sanghyeok Choi, Nayeli Gast Zepeda, André Hottung, Jianan Zhou, Jieyi Bi, Yu Hu, Fei Liu, Hyeonah Kim, Jiwoo Son, Haeyeon Kim, Davide Angioni, Wouter Kool, Zhiguang Cao, Qingfu Zhang, Joungho Kim, Jie Zhang, Kijung Shin, Cathy Wu, Sungsoo Ahn, Guojie Song, Changhyun Kwon, Kevin Tierney, Lin Xie, Jinkyoo Park
2025 J jnl
Sequential Data Augmentation for Generative Recommendation.
CoRR
Geon Lee, Bhuvesh Kumar, Clark Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, Liam Collins
2025 A* conf
Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts.
ICDE
Jongha Lee, Taehyung Kwon, Heechan Moon, Kijung Shin
2025 J jnl
Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts.
CoRR
Jongha Lee, Taehyung Kwon, Heechan Moon, Kijung Shin
2025 — conf
SkySearch: Satellite Video Search at Scale.
KDD (2)
Minyoung Choe, Geon Lee, Changhun Han, Suji Kim, Woong Hu, Hyebeen Hwang, Geunseok Park, Byeongyeon Kim, Hyesook Lee, Ha-Myung Park, Kijung Shin
2025 J jnl
TiGer: Self-Supervised Purification for Time-evolving Graphs.
CoRR
Hyeonsoo Jo, Jongha Lee, Fanchen Bu, Kijung Shin
2025 — conf
TiGer: Self-supervised Purification for Time-Evolving Graphs.
PAKDD (2)
Hyeonsoo Jo, Jongha Lee, Fanchen Bu, Kijung Shin
2025 A* conf
TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents.
AAAI
Geon Lee, Wenchao Yu, Kijung Shin, Wei Cheng, Haifeng Chen
2025 J jnl
TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents.
CoRR
Geon Lee, Wenchao Yu, Kijung Shin, Wei Cheng, Haifeng Chen
2024 J jnl
A Survey on Hypergraph Mining: Patterns, Tools, and Generators.
CoRR
Geon Lee, Fanchen Bu, Tina Eliassi-Rad, Kijung Shin
2024 A* conf
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide.
KDD
Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
2024 J jnl
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide.
CoRR
Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
2024 A* conf
Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors.
KDD
Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, Kijung Shin
2024 A* conf
ELiCiT: Effective and Lightweight Lossy Compression of Tensors.
ICDM
Jihoon Ko, Taehyung Kwon, Jinhong Jung, Kijung Shin
2024 J jnl
Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms.
CoRR
Fanchen Bu, Ruochen Yang, Paul Bogdan, Kijung Shin
2024 A* conf
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective.
ICML
Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin
2024 J jnl
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective.
CoRR
Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin
2024 A* conf
FlowerFormer: Empowering Neural Architecture Encoding Using a Flow-Aware Graph Transformer.
CVPR
Dongyeong Hwang, Hyunju Kim, Sunwoo Kim, Kijung Shin
2024 J jnl
FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer.
CoRR
Dongyeong Hwang, Hyunju Kim, Sunwoo Kim, Kijung Shin
2024 A* conf
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs.
ICLR
Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin
2024 J jnl
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs.
CoRR
Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin
2024 J jnl
Hypergraph motifs and their extensions beyond binary.
VLDB J.
Geon Lee, Seokbum Yoon, Jihoon Ko, Hyunju Kim, Kijung Shin
2024 A conf
Post-Training Embedding Enhancement for Long-Tail Recommendation.
CIKM
Geon Lee, Kyungho Kim, Kijung Shin
2024 — conf
Prediction Is NOT Classification: On Formulation and Evaluation of Hyperedge Prediction.
ICDM (Workshops)
Taehyung Yu, Soo Yong Lee, Hyunjin Hwang, Kijung Shin
2024 J jnl
Random walk with restart on hypergraphs: fast computation and an application to anomaly detection.
Data Min. Knowl. Discov.
Jaewan Chun, Geon Lee, Kijung Shin, Jinhong Jung
2024 J jnl
Representative and Back-In-Time Sampling from Real-world Hypergraphs.
ACM Trans. Knowl. Discov. Data
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin
2024 A* conf
Resource2Box: Learning To Rank Resources in Distributed Search Using Box Embedding.
ICDM
Ulugbek Ergashev, Geon Lee, Kijung Shin, Eduard C. Dragut, Weiyi Meng
2024 A* conf
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy.
NeurIPS
Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, Kijung Shin
2024 J jnl
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy.
CoRR
Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, Kijung Shin
2024 A conf
Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation.
RecSys
Geon Lee, Kyungho Kim, Kijung Shin
2024 A* conf
SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning.
KDD
Jongha Lee, Sunwoo Kim, Kijung Shin
2024 J jnl
SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning.
CoRR
Jongha Lee, Sunwoo Kim, Kijung Shin
2024 A* conf
Self-Guided Robust Graph Structure Refinement.
WWW
Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park
2024 J jnl
Self-Guided Robust Graph Structure Refinement.
CoRR
Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park
2024 A* conf
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs.
ICML
Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, Yuan Qi
2024 J jnl
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs.
CoRR
Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, Yuan Qi
2024 A* conf
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs.
AAAI
Dongjin Lee, Juho Lee, Kijung Shin
2024 A* conf
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More.
ICML
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin
2024 J jnl
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More.
CoRR
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin
2024 A conf
Towards Better Utilization of Multiple Views for Bundle Recommendation.
CIKM
Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin
2024 A* conf
Unsupervised Alignment of Hypergraphs with Different Scales.
KDD
Manh Tuan Do, Kijung Shin
2024 A* conf
VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation.
AAAI
Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin, Sang-Wook Kim
2024 A* conf
VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation.
WWW
Geon Lee, Soo Yong Lee, Kijung Shin
2023 A* conf
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes.
WWW
Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin
2023 J jnl
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes.
CoRR
Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin
2023 A* conf
Classification of Edge-dependent Labels of Nodes in Hypergraphs.
KDD
Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin
2023 J jnl
Classification of Edge-dependent Labels of Nodes in Hypergraphs.
CoRR
Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin
2023 J jnl
Datasets, tasks, and training methods for large-scale hypergraph learning.
Data Min. Knowl. Discov.
Sunwoo Kim, Dongjin Lee, Yul Kim, Jungho Park, Taeho Hwang, Kijung Shin
2023 A* conf
Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding.
WWW
Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim
2023 J jnl
Four-set Hypergraphlets for Characterization of Directed Hypergraphs.
CoRR
Heechan Moon, Hyunju Kim, Sunwoo Kim, Kijung Shin
2023 J jnl
Graphlets over Time: A New Lens for Temporal Network Analysis.
CoRR
Deukryeol Yoon, Dongjin Lee, Minyoung Choe, Kijung Shin
2023 A* conf
How Transitive Are Real-World Group Interactions? - Measurement and Reproduction.
KDD
Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin
2023 J jnl
How Transitive Are Real-World Group Interactions? - Measurement and Reproduction.
CoRR
Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin
2023 J jnl
Hypercore Decomposition for Non-Fragile Hyperedges: Concepts, Algorithms, Observations, and Applications.
CoRR
Fanchen Bu, Geon Lee, Kijung Shin
2023 J jnl
Hypercore decomposition for non-fragile hyperedges: concepts, algorithms, observations, and applications.
Data Min. Knowl. Discov.
Fanchen Bu, Geon Lee, Kijung Shin
2023 J jnl
Hypergraph Motifs and Their Extensions Beyond Binary.
CoRR
Geon Lee, Seokbum Yoon, Jihoon Ko, Hyunju Kim, Kijung Shin
2023 A* conf
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs.
AAAI
Dongjin Lee, Kijung Shin
2023 J jnl
Improving the core resilience of real-world hypergraphs.
Data Min. Knowl. Discov.
Manh Tuan Do, Kijung Shin
2023 J jnl
Interplay between Topology and Edge Weights in Real-World Graphs: Concepts, Patterns, and an Algorithm.
CoRR
Fanchen Bu, Shinhwan Kang, Kijung Shin
2023 J jnl
Interplay between topology and edge weights in real-world graphs: concepts, patterns, and an algorithm.
Data Min. Knowl. Discov.
Fanchen Bu, Shinhwan Kang, Kijung Shin
2023 A* conf
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators.
KDD
Geon Lee, Jaemin Yoo, Kijung Shin
2023 A* conf
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors.
WWW
Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin
2023 J jnl
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors.
CoRR
Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin
2023 A* conf
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms.
KDD
Fanchen Bu, Kijung Shin
2023 J jnl
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms.
CoRR
Fanchen Bu, Kijung Shin
2023 J jnl
Reciprocity in directed hypergraphs: measures, findings, and generators.
Data Min. Knowl. Discov.
Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin
2023 A conf
Robust Graph Clustering via Meta Weighting for Noisy Graphs.
CIKM
Hyeonsoo Jo, Fanchen Bu, Kijung Shin
2023 J jnl
Robust Graph Clustering via Meta Weighting for Noisy Graphs.
CoRR
Hyeonsoo Jo, Fanchen Bu, Kijung Shin
2023 A conf
Robust and Efficient Alignment of Calcium Imaging Data through Simultaneous Low Rank and Sparse Decomposition.
WACV
Junmo Cho, Seungjae Han, Eun-Seo Cho, Kijung Shin, Young-Gyu Yoon
2023 J jnl
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs.
CoRR
Dongjin Lee, Juho Lee, Kijung Shin
2023 J jnl
Temporal hypergraph motifs.
Knowl. Inf. Syst.
Geon Lee, Kijung Shin
2023 A* conf
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions.
ICDM
Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin
2023 J jnl
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions.
CoRR
Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin
2023 A* conf
Towards Deep Attention in Graph Neural Networks: Problems and Remedies.
ICML
Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin
2023 J jnl
Towards Deep Attention in Graph Neural Networks: Problems and Remedies.
CoRR
Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin
2023 — conf
Tutorials at The Web Conference 2023.
WWW (Companion Volume)
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 R. 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
2023 J jnl
Two-Stage Training of Graph Neural Networks for Graph Classification.
Neural Process. Lett.
Manh Tuan Do, Noseong Park, Kijung Shin
2023 J jnl
VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation.
CoRR
Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin, Sang-Wook Kim
2023 A conf
You're Not Alone in Battle: Combat Threat Analysis Using Attention Networks and a New Open Benchmark.
CIKM
Soo Yong Lee, Juwon Kim, Kiwoong Park, Dong Kuk Ryu, Sang Heun Shim, Kijung Shin
2022 A* conf
AHP: Learning to Negative Sample for Hyperedge Prediction.
SIGIR
Hyunjin Hwang, Seungwoo Lee, Chanyoung Park, Kijung Shin
2022 J jnl
AHP: Learning to Negative Sample for Hyperedge Prediction.
CoRR
Hyunjin Hwang, Seungwoo Lee, Chanyoung Park, Kijung Shin
2022 — conf
Are Edge Weights in Summary Graphs Useful? - A Comparative Study.
PAKDD (1)
Shinhwan Kang, Kyuhan Lee, Kijung Shin
2022 J jnl
Are Edge Weights in Summary Graphs Useful? - A Comparative Study.
CoRR
Shinhwan Kang, Kyuhan Lee, Kijung Shin
2022 J jnl
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning.
CoRR
Jihoon Ko, Shinhwan Kang, Kijung Shin
2022 — conf
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data.
ICDM (Workshops)
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Kijung Shin
2022 J jnl
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data.
CoRR
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Kijung Shin
2022 A conf
Directed Network Embedding with Virtual Negative Edges.
WSDM
Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim
2022 J jnl
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation.
CoRR
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Seok-Geun Oh, Seok-Woo Son, Kijung Shin
2022 J jnl
Effective training strategies for deep-learning-based precipitation nowcasting and estimation.
Comput. Geosci.
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Seok-Geun Oh, Seok-Woo Son, Kijung Shin
2022 A conf
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs.
WSDM
Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin
2022 J jnl
Growth patterns and models of real-world hypergraphs.
Knowl. Inf. Syst.
Jihoon Ko, Yunbum Kook, Kijung Shin
2022 A* conf
HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams.
IJCAI
Geon Lee, Minyoung Choe, Kijung Shin
2022 J jnl
HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams.
CoRR
Geon Lee, Minyoung Choe, Kijung Shin
2022 J jnl
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs.
CoRR
Dongjin Lee, Kijung Shin
2022 A conf
MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation.
CIKM
Taeri Kim, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim
2022 A* conf
Meta-Learning for Online Update of Recommender Systems.
AAAI
Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee
2022 J jnl
Meta-Learning for Online Update of Recommender Systems.
CoRR
Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee
2022 A* conf
MiDaS: Representative Sampling from Real-world Hypergraphs.
WWW
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin
2022 J jnl
MiDaS: Representative Sampling from Real-world Hypergraphs.
CoRR
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin
2022 A conf
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators.
CIKM
Geon Lee, Jaemin Yoo, Kijung Shin
2022 A conf
On the Persistence of Higher-Order Interactions in Real-World Hypergraphs.
SDM
Hyunjin Choo, Kijung Shin
2022 J jnl
On the Persistence of Higher-Order Interactions in Real-World Hypergraphs.
CoRR
Hyunjin Choo, Kijung Shin
2022 A* conf
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications.
ICDE
Shinhwan Kang, Kyuhan Lee, Kijung Shin
2022 J jnl
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications.
CoRR
Shinhwan Kang, Kyuhan Lee, Kijung Shin
2022 J jnl
Real-Time Anomaly Detection in Edge Streams.
ACM Trans. Knowl. Discov. Data
Siddharth Bhatia, Rui Liu, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos
2022 A* conf
Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators.
ICDM
Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin
2022 J jnl
Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators.
CoRR
Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin
2022 J jnl
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition.
CoRR
Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin, Deukryeol Yoon, Seongha Eom, Kijung Shin, Se-Young Yun
2022 A* conf
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs.
ICDE
Kyuhan Lee, Jihoon Ko, Kijung Shin
2022 A* conf
Set2Box: Similarity Preserving Representation Learning for Sets.
ICDM
Geon Lee, Chanyoung Park, Kijung Shin
2022 J jnl
Set2Box: Similarity Preserving Representation Learning of Sets.
CoRR
Geon Lee, Chanyoung Park, Kijung Shin
2021 J jnl
CoCoS: Fast and Accurate Distributed Triangle Counting in Graph Streams.
ACM Trans. Knowl. Discov. Data
Kijung Shin, Euiwoong Lee, Jinoh Oh, Mohammad Hammoud, Christos Faloutsos
2021 A conf
DPGS: Degree-Preserving Graph Summarization.
SDM
Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng
2021 — conf
Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data.
MICCAI (7)
Seungjae Han, Eun-Seo Cho, Inkyu Park, Kijung Shin, Young-Gyu Yoon
2021 J jnl
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs.
CoRR
Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin
2021 A* conf
How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators.
WWW
Geon Lee, Minyoung Choe, Kijung Shin
2021 J jnl
How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators.
CoRR
Geon Lee, Minyoung Choe, Kijung Shin
2021 J jnl
Learning to Pool in Graph Neural Networks for Extrapolation.
CoRR
Jihoon Ko, Taehyung Kwon, Kijung Shin, Juho Lee
2021 A* conf
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation.
AAAI
Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee
2021 A* conf
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers.
ICDE
Dongjin Lee, Kijung Shin
2021 J jnl
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers.
CoRR
Dongjin Lee, Kijung Shin
2021 J jnl
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs.
CoRR
Kyuhan Lee, Jihoon Ko, Kijung Shin
2021 A* conf
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams.
ICDE
Taehyung Kwon, Inkyu Park, Dongjin Lee, Kijung Shin
2021 J jnl
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams.
CoRR
Taehyung Kwon, Inkyu Park, Dongjin Lee, Kijung Shin
2021 A* conf
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting.
ICDM
Geon Lee, Kijung Shin
2021 J jnl
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting.
CoRR
Geon Lee, Kijung Shin
2021 — conf
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts.
NeurIPS (Competition and Demos)
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
2020 A* conf
Evolution of Real-world Hypergraphs: Patterns and Models without Oracles.
ICDM
Yunbum Kook, Jihoon Ko, Kijung Shin
2020 J jnl
Evolution of Real-world Hypergraphs: Patterns and Models without Oracles.
CoRR
Yunbum Kook, Jihoon Ko, Kijung Shin
2020 J jnl
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach.
CoRR
Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos
2020 J jnl
Fast and memory-efficient algorithms for high-order Tucker decomposition.
Knowl. Inf. Syst.
Jiyuan Zhang, Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, Hwanjo Yu
2020 J jnl
Fast, Accurate and Provable Triangle Counting in Fully Dynamic Graph Streams.
ACM Trans. Knowl. Discov. Data
Kijung Shin, Sejoon Oh, Jisu Kim, Bryan Hooi, Christos Faloutsos
2020 J jnl
How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction.
CoRR
Se-eun Yoon, HyungSeok Song, Kijung Shin, Yung Yi
2020 A* conf
How Much and When Do We Need Higher-order Informationin Hypergraphs? A Case Study on Hyperedge Prediction.
WWW
Se-eun Yoon, HyungSeok Song, Kijung Shin, Yung Yi
2020 J jnl
Hypergraph Motifs: Concepts, Algorithms, and Discoveries.
CoRR
Geon Lee, Jihoon Ko, Kijung Shin
2020 J jnl
Hypergraph Motifs: Concepts, Algorithms, and Discoveries.
Proc. VLDB Endow.
Geon Lee, Jihoon Ko, Kijung Shin
2020 A* conf
Incremental Lossless Graph Summarization.
KDD
Jihoon Ko, Yunbum Kook, Kijung Shin
2020 J jnl
Incremental Lossless Graph Summarization.
CoRR
Jihoon Ko, Yunbum Kook, Kijung Shin
2020 B conf
MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks.
ASONAM
Jihoon Ko, Kyuhan Lee, Kijung Shin, Noseong Park
2020 J jnl
MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Social Networks.
CoRR
Jihoon Ko, Kyuhan Lee, Kijung Shin, Noseong Park
2020 A* conf
Midas: Microcluster-Based Detector of Anomalies in Edge Streams.
AAAI
Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos
2020 J jnl
Real-Time Streaming Anomaly Detection in Dynamic Graphs.
CoRR
Siddharth Bhatia, Rui Liu, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos
2020 A* conf
SSumM: Sparse Summarization of Massive Graphs.
KDD
Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin
2020 J jnl
SSumM: Sparse Summarization of Massive Graphs.
CoRR
Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin
2020 A* conf
Structural Patterns and Generative Models of Real-world Hypergraphs.
KDD
Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin
2020 J jnl
Structural Patterns and Generative Models of Real-world Hypergraphs.
CoRR
Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin
2020 J jnl
Summarizing graphs using the configuration model.
CoRR
Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng
2020 A* conf
TellTail: Fast Scoring and Detection of Dense Subgraphs.
AAAI
Bryan Hooi, Kijung Shin, Hemank Lamba, Christos Faloutsos
2020 J jnl
Temporal locality-aware sampling for accurate triangle counting in real graph streams.
VLDB J.
Dongjin Lee, Kijung Shin, Christos Faloutsos
2020 J jnl
Two-stage Training of Graph Neural Networks for Graph Classification.
CoRR
Manh Tuan Do, Noseong Park, Kijung Shin
2019 A* conf
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach.
KDD
Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos
2019 J jnl
MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams.
CoRR
Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos
2019 A conf
SMF: Drift-Aware Matrix Factorization with Seasonal Patterns.
SDM
Bryan Hooi, Kijung Shin, Shenghua Liu, Christos Faloutsos
2019 A* conf
SWeG: Lossless and Lossy Summarization of Web-Scale Graphs.
WWW
Kijung Shin, Amol Ghoting, Myunghwan Kim, Hema Raghavan
2018 J jnl
DiSLR: Distributed Sampling with Limited Redundancy For Triangle Counting in Graph Streams.
CoRR
Kijung Shin, Euiwoong Lee, Jinoh Oh, Mohammad Hammoud, Christos Faloutsos
2018 A* conf
Discovering Progression Stages in Trillion-Scale Behavior Logs.
WWW
Kijung Shin, Mahdi Shafiei, Myunghwan Kim, Aastha Jain, Hema Raghavan
2018 J jnl
Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining.
ACM Trans. Knowl. Discov. Data
Kijung Shin, Bryan Hooi, Christos Faloutsos
2018 — conf
ONE-M: Modeling the Co-evolution of Opinions and Network Connections.
ECML/PKDD (2)
Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski, Christos Faloutsos, Nitesh V. Chawla
2018 J jnl
Out-of-Core and Distributed Algorithms for Dense Subtensor Mining.
CoRR
Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos
2018 J jnl
Patterns and anomalies in k-cores of real-world graphs with applications.
Knowl. Inf. Syst.
Kijung Shin, Tina Eliassi-Rad, Christos Faloutsos
2018 — conf
Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions.
ECML/PKDD (2)
Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos
2018 — conf
Tri-Fly: Distributed Estimation of Global and Local Triangle Counts in Graph Streams.
PAKDD (3)
Kijung Shin, Mohammad Hammoud, Euiwoong Lee, Jinoh Oh, Christos Faloutsos
2017 A conf
D-Cube: Dense-Block Detection in Terabyte-Scale Tensors.
WSDM
Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos
2017 A* conf
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams.
KDD
Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos
2017 J jnl
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams.
CoRR
Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos
2017 J jnl
Fully Scalable Methods for Distributed Tensor Factorization.
IEEE Trans. Knowl. Data Eng.
Kijung Shin, Lee Sael, U Kang
2017 J jnl
Graph-Based Fraud Detection in the Face of Camouflage.
ACM Trans. Knowl. Discov. Data
Bryan Hooi, Kijung Shin, Hyun Ah Song, Alex Beutel, Neil Shah, Christos Faloutsos
2017 A conf
S-HOT: Scalable High-Order Tucker Decomposition.
WSDM
Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, Hwanjo Yu
2017 A* conf
WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams.
ICDM
Kijung Shin
2017 J jnl
WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams.
CoRR
Kijung Shin
2017 A* conf
Why You Should Charge Your Friends for Borrowing Your Stuff.
IJCAI
Kijung Shin, Euiwoong Lee, Dhivya Eswaran, Ariel D. Procaccia
2017 J jnl
Why You Should Charge Your Friends for Borrowing Your Stuff.
CoRR
Kijung Shin, Euiwoong Lee, Dhivya Eswaran, Ariel D. Procaccia
2017 — conf
zooRank: Ranking Suspicious Entities in Time-Evolving Tensors.
ECML/PKDD (1)
Hemank Lamba, Bryan Hooi, Kijung Shin, Christos Faloutsos, Jürgen Pfeffer
2016 A* conf
CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms.
ICDM
Kijung Shin, Tina Eliassi-Rad, Christos Faloutsos
2016 A* conf
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage.
KDD
Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos
2016 — conf
Incorporating Side Information in Tensor Completion.
WWW (Companion Volume)
Hemank Lamba, Vaishnavh Nagarajan, Kijung Shin, Naji Shajarisales
2016 — conf
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees.
ECML/PKDD (1)
Kijung Shin, Bryan Hooi, Christos Faloutsos
2016 J jnl
Random Walk with Restart on Large Graphs Using Block Elimination.
ACM Trans. Database Syst.
Jinhong Jung, Kijung Shin, Lee Sael, U Kang
2015 — conf
BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs.
SIGMOD Conference
Kijung Shin, Jinhong Jung, Lee Sael, U Kang
2014 A conf
Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression.
CIKM
Dongyeop Kang, Woosang Lim, Kijung Shin, Lee Sael, U Kang
2014 A* conf
Distributed Methods for High-Dimensional and Large-Scale Tensor Factorization.
ICDM
Kijung Shin, U Kang
2014 J jnl
Distributed Methods for High-dimensional and Large-scale Tensor Factorization.
CoRR
Kijung Shin, U Kang