TPA: Two Phase Approximation for Random Walk with Restart. - Minji Yoon; Jinhong Jung; U Kang (CoRR, 2017)

PMV: Pre-partitioned Generalized Matrix-Vector Multiplication for Scalable Graph Mining. - Chiwan Park; Ha-Myung Park; Minji Yoon; U Kang (CoRR, 2017)

TPA: Fast, Scalable, and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs. - Minji Yoon; Jinhong Jung; U Kang (ICDE, 2018)

Fast and Accurate Random Walk with Restart on Dynamic Graphs with Guarantees. - Minji Yoon; Woojeong Jin 001; U Kang (WWW, 2018)

Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. - Minji Yoon; Bryan Hooi; Kijung Shin; Christos Faloutsos (KDD, 2019)

Midas: Microcluster-Based Detector of Anomalies in Edge Streams. - Siddharth Bhatia 001; Bryan Hooi; Minji Yoon; Kijung Shin; Christos Faloutsos (AAAI, 2020)

Provably Robust Node Classification via Low-Pass Message Passing. - Yiwei Wang 001; Shenghua Liu; Minji Yoon; Hemank Lamba; Wei Wang 059; Christos Faloutsos; Bryan Hooi (ICDM, 2020)

Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off. - Minji Yoon; Théophile Gervet; Bryan Hooi; Christos Faloutsos (ICDM, 2020)

Real-Time Streaming Anomaly Detection in Dynamic Graphs. - Siddharth Bhatia 001; Rui Liu 004; Bryan Hooi; Minji Yoon; Kijung Shin; Christos Faloutsos (CoRR, 2020)

Performance-Adaptive Sampling Strategy Towards Fast and Accurate Graph Neural Networks. - Minji Yoon; Théophile Gervet; Baoxu Shi; Sufeng Niu; Qi He 002; Jaewon Yang (KDD, 2021)

Graph Fraud Detection Based on Accessibility Score Distributions. - Minji Yoon (ECML/PKDD (2), 2021)

Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. - Minji Yoon; John Palowitch; Dustin Zelle; Ziniu Hu; Ruslan Salakhutdinov; Bryan Perozzi (NeurIPS, 2022)

Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. - Minji Yoon; John Palowitch; Dustin Zelle; Ziniu Hu; Ruslan Salakhutdinov; Bryan Perozzi (CoRR, 2022)

Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. - Minji Yoon; Yue Wu 001; John Palowitch; Bryan Perozzi; Ruslan Salakhutdinov (CoRR, 2022)

Autonomous graph mining algorithm search with best performance trade-off. - Minji Yoon; Théophile Gervet; Bryan Hooi; Christos Faloutsos (Knowl. Inf. Syst., 2022)

Real-Time Anomaly Detection in Edge Streams. - Siddharth Bhatia 001; Rui Liu 004; Bryan Hooi; Minji Yoon; Kijung Shin; Christos Faloutsos (ACM Trans. Knowl. Discov. Data, 2022)

Graph Generative Model for Benchmarking Graph Neural Networks. - Minji Yoon; Yue Wu 001; John Palowitch; Bryan Perozzi; Russ Salakhutdinov (ICML, 2023)

A Dataset on Malicious Paper Bidding in Peer Review. - Steven Jecmen; Minji Yoon; Vincent Conitzer; Nihar B. Shah; Fei Fang 001 (WWW, 2023)

Multimodal Graph Learning for Generative Tasks. - Minji Yoon; Jing Yu Koh; Bryan Hooi; Ruslan Salakhutdinov (CoRR, 2023)

Automatic Question-Answer Generation for Long-Tail Knowledge. - Rohan Kumar; Youngmin Kim; Sunitha Ravi; Haitian Sun; Christos Faloutsos; Ruslan Salakhutdinov; Minji Yoon (CoRR, 2024)

Deep Learning on Graphs: Tackling Scalability, Privacy, and Multimodality - Minji Yoon (2024)