[C73] A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide

Sunwoo Kim*, Soo Yong Lee*, Yue Gao, Alessia Antelmi, Mirko Polato, and Kijung Shin

KDD 2024 (Survey Paper): ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2024

[C72] Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors

Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, and Kijung Shin

KDD 2024: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2024

[C71] SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning

Jongha Lee, Sunwoo Kim, and Kijung Shin

KDD 2024: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2024

[C70] Unsupervised Alignment of Hypergraphs with Different Scales

Manh Tuan Do and Kijung Shin

KDD 2024: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2024

[C69] Tackling Complex Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More

Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, and Kijung Shin

ICML 2024: International Conference on Machine Learning 2024

[C68] Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective

Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, and Kijung Shin

ICML 2024: International Conference on Machine Learning 2024

[C67] Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs

Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, and Yuan Qi

ICML 2024: International Conference on Machine Learning 2024

[C66] FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer

Dongyeong Hwang, Hyunju Kim, Sunwoo Kim, and Kijung Shin

CVPR 2024: IEEE/CVF Computer Vision and Pattern Recognition Conference 2024

[C65] VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation

Geon Lee, Soo Yong Lee, and Kijung Shin

WWW 2024: The Web Conference 2024

[C64] Self-Guided Robust Graph Structure Refinement

Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, and Chanyoung Park

WWW 2024: The Web Conference 2024

[C63] HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs

Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, and Kijung Shin

ICLR 2024: International Conference on Learning Representations 2024

[C62] Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs

Dongjin Lee, Juho Lee, and Kijung Shin

AAAI 2024: AAAI Conference on Artificial Intelligence 2024

[C61] VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation

Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin, and Sang-Wook Kim

AAAI 2024: AAAI Conference on Artificial Intelligence 2024

Selected for oral presentation (2.6% of accepted papers) 

[J25] Representative and Back-In-Time Sampling from Real-world Hypergraphs

Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, and Kijung Shin

ACM TKDD: ACM Transactions on Knowledge Discovery from Data

[J24] Deep Learning Model for Heavy Rainfall Nowcasting in South Korea

Seok-Geun Oh, Seok-Woo Son, Young-Ha Kim, Chanil Park , Jihoon Ko, Kijung Shin, Ji-Hoon Ha, and Hyesook Lee

Weather and Climate Extremes

[J23] Random Walk with Restart on Hypergraphs: Fast Computation and an Application to Anomaly Detection

Jaewan Chun, Geon Lee, Kijung Shin, and Jinhong Jung

Data Mining and Knowledge Discovery

[C60] TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions

Taehyung Kwon, Jihoon Ko, Jinhong Jung, and Kijung Shin

ICDM 2023:  IEEE International Conference on Data Mining 2023

Received the IEEE ICDM Best Student Paper Runner-up Award [link]

Selected as one of the best-ranked papers of ICDM 2023 for fast-track journal invitation 

[C59] Robust Graph Clustering via Meta Weighting for Noisy Graphs

Hyeonsoo Jo, Fanchen Bu, and Kijung Shin

CIKM 2023: ACM International Conference on Information and Knowledge Management 2023

[C58] You’re Not Alone in Battle: Combat Threat Analysis Using Attention Networks and a New Open Benchmark

Soo Yong Lee*, Juwon Kim*, Kiwoong Park, Dongkuk Ryu, Sangheun Shim, and Kijung Shin

CIKM 2023 (Short Paper): ACM International Conference on Information and Knowledge Management 2023

[C57] How Transitive Are Real-World Group Interactions? - Measurement and Reproduction

Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, and Kijung Shin

KDD 2023: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2023

[C56] On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithm

Fanchen Bu and Kijung Shin

KDD 2023: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2023

[C55] Classification of Edge-dependent Labels of Nodes in Hypergraphs

Minyoung Choe, Sunwoo Kim, Jaemin Yoo, and Kijung Shin

KDD 2023: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2023

[C54] Towards Deep Attention in Graph Neural Networks: Problems and Remedies

Soo Yong Lee, Fanchen Bu, Jaemin Yoo, and Kijung Shin

ICML 2023: International Conference on Machine Learning 2023

[C53] NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors

Taehyung Kwon*, Jihoon Ko*, Jinhong Jung, and Kijung Shin

WWW 2023: The Web Conference 2023

[C52] Characterization of Simplicial Complexes Using Simplets Beyond Four Nodes

Hyunju Kim, Jihoon Ko, Fanchen Bu, and Kijung Shin

WWW 2023:  The Web Conference 2023

[C51] Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding

Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, and Sang-Wook Kim

WWW 2023: The Web Conference 2023

[C50] I'm Me, We're Us, and I'm Us: Tridirectional Contrastive Learning on Hypergraphs

Dongjin Lee and Kijung Shin

AAAI 2023: AAAI Conference on Artificial Intelligence 2023

[C49] Robust and Efficient Alignment of Calcium Imaging Data through Simultaneous Low Rank and Sparse Decomposition

Junmo Cho*, Seungjae Han*, Eun-Seo Cho, Kijung Shin, and Young-Gyu Yoon

WACV 2023: IEEE/CVF Winter Conference on Applications of Computer Vision 2023

[J21] Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators

Sunwoo Kim, Minyoung Choe, Jaemin Yoo, and Kijung Shin

Data Mining and Knowledge Discovery

[J20] Datasets, Tasks, and Training Methods for Large-Scale Hypergraph Learning

Sunwoo Kim*, Dongjin Lee*, Yul Kim, Jungho Park, Taeho Hwang, and Kijung Shin

Data Mining and Knowledge Discovery

[J19] Improving the Core Resilience of Real-world Hypergraphs

Manh Tuan Do and Kijung Shin

Data Mining and Knowledge Discovery

[J18] Hypercore Decomposition for Non-Fragile Hyperedges: Concepts, Algorithms, Observations, and Applications

Fanchen Bu, Geon Lee, and Kijung Shin

Data Mining and Knowledge Discovery

[J17] Interplay between Topology and Edge Weights in Real-World Graphs: Concepts, Patterns, and an Algorithm

Fanchen Bu, Shinhwan Kang, and Kijung Shin

Data Mining and Knowledge Discovery

[J16] Temporal Hypergraph Motifs

Geon Lee and Kijung Shin

Knowledge and Information Systems

[J15] Evaluation of Deep-Learning-Based Very Short-Term Rainfall Forecasts in South Korea

Seok-Geun Oh , Chanil Park, Seok-Woo Son, Jihoon Ko, Kijung Shin, Sunyoung Kim, and Junsang Park

Asia-Pacific Journal of Atmospheric Sciences

[C48] Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators

Sunwoo Kim, Minyoung Choe, Jaemin Yoo, and Kijung Shin

ICDM 2022: IEEE International Conference on Data Mining 2022

[C47] Set2Box: Similarity Preserving Representation Learning for Sets

Geon Lee, Chanyoung Park, and Kijung Shin

ICDM 2022: IEEE International Conference on Data Mining 2022

[C46] MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation

Taeri Kim*, Yeon-Chang Lee*, Kijung Shin, and Sang-Wook Kim

CIKM 2022: ACM International Conference on Information and Knowledge Management 2022

[C45] HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams

Geon Lee, Minyoung Choe, and Kijung Shin

IJCAI 2022: International Joint Conference on Artificial Intelligence 2022

[C44] AHP: Learning to Negative Sample for Hyperedge Prediction

Hyunjin Hwang*, Seungwoo Lee*, Chanyoung Park, and Kijung Shin

SIGIR 2022 (Short Paper): International ACM SIGIR Conference on Research and Development in Information Retrieval 2022

[C43] Are Edge Weights in Summary Graphs Useful? - A Comparative Study

Shinhwan Kang, Kyuhan Lee, and Kijung Shin

PAKDD 2022:  Pacific-Asia Conference on Knowledge Discovery and Data Mining 2022

[C42] Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications

Shinhwan Kang, Kyuhan Lee, and Kijung Shin

ICDE 2022: IEEE International Conference on Data Engineering 2022

[C41] SLUGGER: Lossless Hierarchical Summarization of Massive Graphs

Kyuhan Lee*, Jihoon Ko*, and Kijung Shin

ICDE 2022: IEEE International Conference on Data Engineering 2022

[C40] MiDaS: Representative Sampling from Real-world Hypergraphs

Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, and Kijung Shin

WWW 2022: The Web Conference 2022

[C39] On the Persistence of Higher-Order Interactions in Real-World Hypergraphs

Hyunjin Choo and Kijung Shin

SDM 2022: SIAM International Conference on Data Mining 2022

[C38] Meta-Learning for Online Update of Recommender Systems

Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, and Jae-Gil Lee

AAAI 2022: AAAI Conference on Artificial Intelligence 2022

[C37] Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs

Hyeonjeong Shin, Taehyung Kwon, Neil Shah, and Kijung Shin

WSDM 2022: ACM International Conference on Web Search and Data Mining 2022

[C36] Directed Network Embedding with Virtual Negative Edges

Hyunsik Yoo*, Yeon-Chang Lee*, Kijung Shin, and Sang-Wook Kim

WSDM 2022: ACM International Conference on Web Search and Data Mining 2022

[J13] Growth Patterns and Models of Real-world Hypergraphs

Jihoon Ko*, Yunbum Kook*, and Kijung Shin

Knowledge and Information Systems

[J12] Effective Training Strategies for Deep Learning-Based Precipitation Nowcasting and Estimation

Jihoon Ko*, Kyuhan Lee*, Hyunjin Hwang*, Seok-Geun Oh, Seok-Woo Son, and Kijung Shin

Computers and Geosciences

[J11] Simple Epidemic Models with Segmentation Can Be Better than Complex Ones

Geon Lee, Se-eun Yoon, and Kijung Shin

PLOS ONE

[C35] THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting

Geon Lee and Kijung Shin

ICDM 2021: IEEE International Conference on Data Mining 2021

Selected as one of the best-ranked papers of ICDM 2021 for fast-track journal invitation 

[C34] Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data

Seungjae Han, Eun-Seo Cho, Inkyu Park, Kijung Shin, and Young-Gyu Yoon

MICCAI 2021: International Conference on Medical Image Computing and Computer Assisted Intervention 2021

[C33] SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams

Taehyung Kwon*, Inkyu Park*, Dongjin Lee, and Kijung Shin

ICDE 2021: IEEE International Conference on Data Engineering 2021

[C32] Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers

Dongjin Lee and Kijung Shin

ICDE 2021: IEEE International Conference on Data Engineering 2021

[C31] How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators

Geon Lee*, Minyoung Choe*, and Kijung Shin

WWW 2021: The Web Conference 2021

[C30] PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation

Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, and Jae-Gil Lee

AAAI 2021: AAAI Conference on Artificial Intelligence 2021

[C29] DPGS: Degree-Preserving Graph Summarization

Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, and Xueqi Cheng

SDM 2021: SIAM International Conference on Data Mining 2021

[C28] MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks

Jihoon Ko, Kyuhan Lee, Kijung Shin, and Noseong Park

ASONAM 2020: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2020

Selected for fast-track journal invitation 

[C27] Evolution of Real-world Hypergraphs: Patterns and Models without Oracles

Yunbum Kook, Jihoon Ko, and Kijung Shin

ICDM 2020: IEEE International Conference on Data Mining 2020

Selected as one of the best-ranked papers of ICDM 2020 for fast-track journal invitation 

[C26]  Hypergraph Motifs: Concepts, Algorithms, and Discoveries

Geon Lee, Jihoon Ko, and Kijung Shin

VLDB 2020: International Conference on Very Large Data Bases 

[C25]  Incremental Lossless Graph Summarization

Jihoon Ko*, Yunbum Kook*, and Kijung Shin 

KDD 2020: ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2020

[C24]  SSumM: Sparse Summarization of Massive Graphs

Kyuhan Lee*, Hyeonsoo Jo*, Jihoon Ko, Sungsu Lim, and Kijung Shin 

KDD 2020: ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2020

[C23]  Structural Patterns and Generative Models of Real-world Hypergraphs

Manh Tuan Do, Se-eun Yoon, Bryan Hooi, and Kijung Shin

KDD 2020: ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2020

[C22] How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction

Se-eun Yoon, Hyungseok Song, Kijung Shin, and Yung Yi

WWW 2020 (Short Paper): The Web Conference 2020

[C21]  TellTail: Fast Scoring and Detection of Dense Subgraphs

Bryan Hooi, Kijung Shin, Hemank Lamba, and Christos Faloutsos

AAAI 2020: AAAI Conference on Artificial Intelligence 2020

[C20]  MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams 

Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, and Christos Faloutsos

AAAI 2020: AAAI Conference on Artificial Intelligence 2020

[J8]  Temporal Locality-Aware Sampling for Accurate Triangle Counting in Real Graph Streams

Dongjin Lee, Kijung Shin, and Christos Faloutsos 

The VLDB Journal

[J7]  Fast and Memory-Efficient Algorithms for High-Order Tucker Decomposition

Jiyuan Zhang, Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, and Hwanjo Yu

Knowledge and Information Systems  

[C19]  Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach

Minji Yoon, Bryan Hooi, Kijung Shin, and Christos Faloutsos

KDD 2019: ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2019

[C18]  SWeG: Lossless and Lossy Summarization of Web-Scale Graphs

Kijung Shin, Amol Ghoting, Myunghwan Kim, and Hema Raghavan

WWW 2019: The Web Conference 2019

[C16]  Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions

Kijung Shin, Jisu Kim, Bryan Hooi, and Christos Faloutsos

PKDD 2018: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2018

[C15] ONE-M: Modeling the Co-evolution of Opinions and Network Connections

Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen,  Boleslaw Szymanski, Christos Faloutsos, and Nitesh Chawla 

PKDD 2018: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2018

[C14] Discovering Progression Stages in Trillion-Scale Behavior Logs

Kijung Shin, Mahdi Shafiei, Myunghwan Kim, Aastha Jain, and Hema Raghavan

WWW 2018: The Web Conference 2018

[C13] Tri-Fly: Distributed Estimation of Global and Local Triangle Counts in Graph Streams

Kijung Shin, Mohammad Hammoud, Euiwoong Lee, Jinoh Oh, and Christos Faloutsos

PAKDD 2018: Pacific-Asia Conference on Knowledge Discovery and Data Mining 2018

[J5] Fast, Accurate and Flexible Algorithms for Dense Subtensor Mining

Kijung Shin, Bryan Hooi, and Christos Faloutsos

ACM TKDD: ACM Transactions on Knowledge Discovery from Data

[J4] Patterns and Anomalies in k-Cores of Real-World Graphs with Applications

Kijung Shin, Tina Eliassi-Rad, and Christos Faloutsos

Knowledge and Information Systems  

Included in courses: MIT (6.886)

[C12] WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams

Kijung Shin

ICDM 2017: IEEE International Conference on Data Mining 2017

[C11] ZooRank: Ranking Suspicious Entities in Time-Evolving Tensors

Hemank Lamba, Bryan Hooi, Kijung Shin, Christos Faloutsos, and Jürgen Pfeffer

PKDD 2017: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2017

[C10] DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams

Kijung Shin, Bryan Hooi, Jisu Kim, and Christos Faloutsos

KDD 2017: ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2017

[C9] Why You Should Charge Your Friends for Borrowing Your Stuff

Kijung Shin, Euiwoong Lee, Dhivya Eswaran, and Ariel D. Procaccia

IJCAI 2017: International Joint Conference on Artificial Intelligence 2017

Media: New Scientist [link]

[C8] D-Cube: Dense-Block Detection in Terabyte-Scale Tensors

Kijung Shin, Bryan Hooi, Jisu Kim, and Christos Faloutsos

WSDM 2017: ACM International Conference on Web Search and Data Mining 2017

[C7] S-HOT: Scalable High-Order Tucker Decomposition

Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, and Hwanjo Yu

 WSDM 2017: ACM International Conference on Web Search and Data Mining 2017

[J3] Graph-Based Fraud Detection in the Face of Camouflage

Bryan Hooi, Kijung Shin, Hyun Ah Song, Alex Beutel, Neil Shah, and Christos Faloutsos

ACM TKDD: ACM Transactions on Knowledge Discovery from Data

Special Issue on the Best Papers from KDD 2016

[J2] Fully Scalable Methods for Distributed Tensor Factorization

Kijung Shin, Lee Sael, and U Kang

IEEE TKDE: IEEE Transactions on Knowledge and Data Engineering

[C6] CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms

Kijung Shin, Tina Eliassi-Rad, and Christos Faloutsos

ICDM 2016: IEEE International Conference on Data Mining 2016

Selected as one of the best-ranked papers of ICDM 2016 for fast-track journal invitation 

[C5] M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees

Kijung Shin, Bryan Hooi, and Christos Faloutsos

PKDD 2016: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2016

[C4] FRAUDAR: Bounding Graph Fraud in the Face of Camouflage

Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, and Christos Faloutsos

KDD 2016: ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2016 

Received the SIGKDD Best Research Paper Award [link]

Media: NSF [link], WESA [link], TechXplore [link], Stanford Scholar [link], Crain's [link]

[J1] Random Walk with Restart on Large Graphs Using Block Elimination

Jinhong Jung, Kijung Shin, Lee Sael, and U Kang

ACM TODS: ACM Transactions on Database Systems

[C3] BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs

Kijung Shin, Jinhong Jung, Lee Sael, and U Kang

SIGMOD 2015: ACM SIGMOD International Conference on the Management of Data 2015

Received the Samsung Humantech Paper Award (1st in Computer Science)

Included in courses: UMich (EECS 598)