Please visit https://jaeminyoo.github.io for full papers, code, and datasets.

Conference Papers

2025

[c28] Criteria-Aware Graph Filtering: Extremely Fast Yet Accurate Multi-Criteria Recommendation
Jin-Duk Park, Jaemin Yoo, and Won-Yong Shin
The Web Conference (WWW) 2025

[c27] TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection
Boje Deforce, Meng-Chieh Lee, Bart Baesens, Estefanía Serral Asensio, Jaemin Yoo and Leman Akoglu
SIAM International Conference on Data Mining (SDM) 2025

2024

[c26] Rethinking Reconstruction-based Graph-level Anomaly Detectors: Limitations and a Remedy
Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, and Kijung Shin
Conference on Neural Information Processing Systems (NeurIPS) 2024

[c25] 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
International Conference on Machine Learning (ICML) 2024 

[c24] NetEffect: Discovery and Exploitation of Generalized Network Effects
Meng-Chieh Lee, Shubhranshu Shekhar, Jaemin Yoo, and Christos Faloutsos
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2024 

[c23] HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, and Kijung Shin
International Conference on Learning Representations (ICLR) 2024 

2023

[c22] Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities (Short  Paper)
Leman Akoglu and Jaemin Yoo
IEEE International Conference on Big Data (BigData) 2023

[c21] DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, and Leman Akoglu
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2023

[c20] Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Jaemin Yoo*, Meng-Chieh Lee*, Shubhranshu Shekhar, and Christos Faloutsos
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023

[c19] How Transitive Are Real-World Group Interactions? - Measurement and Reproduction
Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, and Kijung Shin
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023

[c18] Classification of Edge-dependent Labels of Nodes in Hypergraphs
Minyoung Choe, Sunwoo Kim, Jaemin Yoo, and Kijung Shin
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023

[c17] Towards Deep Attention in Graph Neural Networks: Problems and Remedies
Soo Yong Lee, Fanchen Bu, Jaemin Yoo, and Kijung Shin
International Conference on Machine Learning (ICML) 2023

2022

[c16] Accurate Stock Movement Prediction with Self-supervised Learning from Sparse Noisy Tweets
Yejun Soun*, Jaemin Yoo*, Minyong Cho, Jihyeong Jeon, and U Kang
IEEE International Conference on Big Data (BigData) 2022

[c15] Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators
Sunwoo Kim, Minyoung Choe, Jaemin Yoo, and Kijung Shin
IEEE International Conference on Data Mining (ICDM) 2022

[c14] Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, and U Kang
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2022

[c13] Model-Agnostic Augmentation for Accurate Graph Classification
Jaemin Yoo, Sooyeon Shim, and U Kang
The Web Conference (WWW) 2022

[c12] MiDaS: Representative Sampling from Real-world Hypergraphs
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, and Kijung Shin
The Web Conference (WWW) 2022

[c11] Transition Matrix Representation of Trees with Transposed Convolutions
Jaemin Yoo and Lee Sael
SIAM International Conference on Data Mining (SDM) 2022

2021

[c10] Accurate Graph-Based PU Learning without Class Prior
Jaemin Yoo*, Junghun Kim*, Hoyoung Yoon*, Geonsoo Kim, Changwon Jang, and U Kang
IEEE International Conference on Data Mining (ICDM) 2021

[c9] Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts
Jaemin Yoo, Yejun Soun, Yong-chan Park, and U Kang
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2021

[c8] Gaussian Soft Decision Trees for Interpretable Feature-Based Classification
Jaemin Yoo and Lee Sael
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2021

[c7] Attention-Based Autoregression for Accurate and Efficient Multivariate Time Series Forecasting
Jaemin Yoo and U Kang
SIAM International Conference on Data Mining (SDM) 2021

2020 and Before

[c6] Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference
Jaemin Yoo, U Kang, Mauro Scanagatta, Giorgio Corani, and Marco Zaffalon
ACM International Conference on Web Search and Data Mining (WSDM) 2020

[c5] Knowledge Extraction with No Observable Data
Jaemin Yoo, Minyong Cho, Taebum Kim, and U Kang
Conference on Neural Information Processing Systems (NeurIPS) 2019

[c4] EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees
Jaemin Yoo and Lee Sael
IEEE International Conference on Data Mining (ICDM) 2019

[c3] Belief Propagation Network for Hard Inductive Semi-Supervised Learning
Jaemin Yoo, Hyunsik Jeon, and U Kang
International Joint Conference on Artificial Intelligence (IJCAI) 2019

[c2] Fast and Scalable Distributed Loopy Belief Propagation on Real-World Graphs
Saehan Jo, Jaemin Yoo, and U Kang
ACM International Conference on Web Search and Data Mining (WSDM) 2018 

[c1] Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks
Jaemin Yoo, Saehan Jo, and U Kang
IEEE International Conference on Data Mining (ICDM) 2017

Journal Papers

[j6] Representative and Back-in-Time Sampling from Real-world Hypergraphs
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, and Kijung Shin
Transactions on Knowledge Discovery from Data 

[j5] Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success
Jaemin Yoo, Tiancheng Zhao, and Leman Akoglu
Transactions on Machine Learning Research

[j4] Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators
Sunwoo Kim, Minyoung Choe, Jaemin Yoo, and Kijung Shin
Data Mining and Knowledge Discovery

[j3] Graph-based PU Learning for Binary and Multiclass Classification without Class Prior
Jaemin Yoo*, Junghun Kim*, Hoyoung Yoon*, Geonsoo Kim, Changwon Jang, and U Kang
Knowledge and Information Systems

[j2] Signed Random Walk Diffusion for Effective Representation Learning in Signed Graphs
Jinhong Jung, Jaemin Yoo, and U Kang
PLOS ONE

[j1] Efficient Learning of Bounded-Treewidth Bayesian Networks from Complete and Incomplete Data Sets
Mauro Scanagatta, Giorgio Corani, Marco Zaffalon, Jaemin Yoo, and U Kang
International Journal of Approximate Reasoning

Tutorials

[t1] Mining of Real-world Hypergraphs: Concepts, Patterns, and Generators
Geon Lee, Jaemin Yoo, and Kijung Shin
IEEE International Conference on Data Mining (ICDM) 2022
ACM International Conference on Information and Knowledge Management (CIKM) 2022
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023
The Web Conference (WWW) 2023