| 2026 | AAAI | Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption. | Sunwoo Kim, Soo Yong Lee, Kyungho Kim, Hyunjin Hwang, Jaemin Yoo, Kijung Shin |
| 2026 | ACL | Pre-Deployment Advertisement Ranking under Data Scarcity via Context-Aware Criteria Generation with VLMs. | Kyungho Kim, Yeonje Choi, Gyurim Hwang, Sejin Chung, Hongseok Lee, Myeong Ho Song, Yeongho Kim, Sunwoo Kim, Jongha Lee, Juyeon Kim, Kijung Shin |
| 2026 | ACL | Hybrid-Vector Retrieval for Visually Rich Documents: Combining Single-Vector Efficiency and Multi-Vector Accuracy. | Juyeon Kim, Geon Lee, Dongwon Choi, Taeuk Kim, Kijung Shin |
| 2026 | ICDE | Effective Dataset Distillation for Spatio-Temporal Forecasting with BI-Dimensional Compression. | Taehyung Kwon, Yeonje Choi, Yeongho Kim, Kijung Shin |
| 2026 | WWW | Personalized Parameter-Efficient Fine-Tuning of Foundation Models for Multimodal Recommendation. | Sunwoo Kim, Hyunjin Hwang, Kijung Shin |
| 2026 | WWW | ReFuGe: Feature Generation for Prediction Tasks on Relational Databases with LLM Agents. | Kyungho Kim, Geon Lee, Juyeon Kim, Dongwon Choi, Shinhwan Kang, Kijung Shin |
| 2026 | SIGIR | ItemRAG: Item-Based Retrieval-Augmented Generation for LLM-Based Recommendation. | Sunwoo Kim, Geon Lee, Kyungho Kim, Jaemin Yoo, Kijung Shin |
| 2026 | SIGIR | From Raw Features to Effective Embeddings: A Three-Stage Approach for Multimodal Recipe Recommendation. | Jeeho Shin, Kyungho Kim, Kijung Shin |
| 2026 | WSDM | Sequential Data Augmentation for Generative Recommendation. | Geon Lee, Bhuvesh Kumar, Mingxuan Ju, Tong Zhao, Kijung Shin, Neil Shah, Liam Collins |
| 2025 | AAAI | DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation. | Junghun Lee, Hyunju Kim, Fanchen Bu, Jihoon Ko, Kijung Shin |
| 2025 | AAAI | TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents. | Geon Lee, Wenchao Yu, Kijung Shin, Wei Cheng, Haifeng Chen |
| 2025 | CIKM | A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation. | Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin |
| 2025 | CIKM | A Tutorial on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. | Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin |
| 2025 | EDBT | RASP: Robust Mining of Frequent Temporal Sequential Patterns under Temporal Variations. | Hyunjin Choo, Minho Eom, Gyuri Kim, Young-Gyu Yoon, Kijung Shin |
| 2025 | EMNLP | 'Hello, World!': Making GNNs Talk with LLMs. | Sunwoo Kim, Soo Yong Lee, Jaemin Yoo, Kijung Shin |
| 2025 | ICDE | Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts. | Jongha Lee, Taehyung Kwon, Heechan Moon, Kijung Shin |
| 2025 | ICDE | MARIOH: Multiplicity-Aware Hypergraph Reconstruction. | Kyuhan Lee, Geon Lee, Kijung Shin |
| 2025 | ICDM | Identifying Group Anchors in Real-World Group Interactions Under Label Scarcity. | Fanchen Bu, Geon Lee, Kijung Shin, Minyoung Choe |
| 2025 | ICDM | Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms. | Fanchen Bu, Ruochen Yang, Paul Bogdan, Kijung Shin |
| 2025 | ICDM | HyperSearch: Prediction of New Hyperedges Through Unconstrained yet Efficient Search. | Hyunjin Choo, Fanchen Bu, Hyunjin Hwang, Young-Gyu Yoon, Kijung Shin |
| 2025 | ICDM | Attributed Hypergraph Generation with Realistic Interplay Between Structure and Attributes. | Jaewan Chun, Seokbum Yoon, Minyoung Choe, Geon Lee, Kijung Shin |
| 2025 | ICML | Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification. | Langzhang Liang, Fanchen Bu, Zixing Song, Zenglin Xu, Shirui Pan, Kijung Shin |
| 2025 | KDD | RL4CO: An Extensive Reinforcement Learning for Combinatorial Optimization Benchmark. | Federico Berto, Chuanbo Hua, Junyoung Park, Laurin Luttmann, Yining Ma, Fanchen Bu, Jiarui Wang, Haoran Ye, Minsu Kim, Sanghyeok Choi, Nayeli Gast Zepeda, Andr 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 | KDD | SkySearch: Satellite Video Search at Scale. | Minyoung Choe, Geon Lee, Changhun Han, Suji Kim, Woong Hu, Hyebeen Hwang, Geunseok Park, Byeongyeon Kim, Hyesook Lee, Ha-Myung Park, Kijung Shin |
| 2025 | KDD | On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications. | Hyeonsoo Jo, Hyunjin Hwang, Fanchen Bu, Soo Yong Lee, Chanyoung Park, Kijung Shin |
| 2025 | PAKDD | TiGer: Self-supervised Purification for Time-Evolving Graphs. | Hyeonsoo Jo, Jongha Lee, Fanchen Bu, Kijung Shin |
| 2025 | PAKDD | Multi-behavior Recommender Systems: A Survey. | Kyungho Kim, Sunwoo Kim, Geon Lee, Jinhong Jung, Kijung Shin |
| 2025 | WWW | Kronecker Generative Models for Power-Law Patterns in Real-World Hypergraphs. | Minyoung Choe, Jihoon Ko, Taehyung Kwon, Kijung Shin, Christos Faloutsos |
| 2025 | WWW | Beyond Neighbors: Distance-Generalized Graphlets for Enhanced Graph Characterization. | Yeongho Kim, Yuyeong Kim, Geon Lee, Kijung Shin |
| 2025 | SIGIR | KGMEL: Knowledge Graph-Enhanced Multimodal Entity Linking. | Juyeon Kim, Geon Lee, Taeuk Kim, Kijung Shin |
| 2024 | AAAI | VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation. | Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin, Sang-Wook Kim |
| 2024 | AAAI | Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs. | Dongjin Lee, Juho Lee, Kijung Shin |
| 2024 | CIKM | Towards Better Utilization of Multiple Views for Bundle Recommendation. | Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin |
| 2024 | CIKM | Post-Training Embedding Enhancement for Long-Tail Recommendation. | Geon Lee, Kyungho Kim, Kijung Shin |
| 2024 | CVPR | FlowerFormer: Empowering Neural Architecture Encoding Using a Flow-Aware Graph Transformer. | Dongyeong Hwang, Hyunju Kim, Sunwoo Kim, Kijung Shin |
| 2024 | ICDM | Resource2Box: Learning To Rank Resources in Distributed Search Using Box Embedding. | Ulugbek Ergashev, Geon Lee, Kijung Shin, Eduard C. Dragut, Weiyi Meng |
| 2024 | ICDM | ELiCiT: Effective and Lightweight Lossy Compression of Tensors. | Jihoon Ko, Taehyung Kwon, Jinhong Jung, Kijung Shin |
| 2024 | ICDM | Prediction Is NOT Classification: On Formulation and Evaluation of Hyperedge Prediction. | Taehyung Yu, Soo Yong Lee, Hyunjin Hwang, Kijung Shin |
| 2024 | ICLR | HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs. | Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin |
| 2024 | ICML | Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More. | Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin |
| 2024 | ICML | Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective. | Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin |
| 2024 | ICML | 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, Yuan Qi |
| 2024 | KDD | Unsupervised Alignment of Hypergraphs with Different Scales. | Manh Tuan Do, Kijung Shin |
| 2024 | KDD | 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, Kijung Shin |
| 2024 | KDD | 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, Kijung Shin |
| 2024 | KDD | SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning. | Jongha Lee, Sunwoo Kim, Kijung Shin |
| 2024 | RecSys | Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation. | Geon Lee, Kyungho Kim, Kijung Shin |
| 2024 | WWW | Self-Guided Robust Graph Structure Refinement. | Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park |
| 2024 | WWW | VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation. | Geon Lee, Soo Yong Lee, Kijung Shin |
| 2023 | AAAI | I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs. | Dongjin Lee, Kijung Shin |
| 2023 | CIKM | Robust Graph Clustering via Meta Weighting for Noisy Graphs. | Hyeonsoo Jo, Fanchen Bu, Kijung Shin |
| 2023 | CIKM | You're Not Alone in Battle: Combat Threat Analysis Using Attention Networks and a New Open Benchmark. | Soo Yong Lee, Juwon Kim, Kiwoong Park, Dong Kuk Ryu, Sang Heun Shim, Kijung Shin |
| 2023 | ICDM | TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions. | Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin |
| 2023 | ICML | Towards Deep Attention in Graph Neural Networks: Problems and Remedies. | Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin |
| 2023 | KDD | On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. | Fanchen Bu, Kijung Shin |
| 2023 | KDD | Classification of Edge-dependent Labels of Nodes in Hypergraphs. | Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin |
| 2023 | KDD | How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. | Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin |
| 2023 | KDD | Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. | Geon Lee, Jaemin Yoo, Kijung Shin |
| 2023 | WWW | Tutorials at The Web Conference 2023. | Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espn-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 Kk-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 | WWW | Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. | Hyunju Kim, Jihoon Ko, Fanchen Bu, Kijung Shin |
| 2023 | WWW | NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors. | Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin |
| 2023 | WWW | Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding. | Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim |
| 2023 | WACV | Robust and Efficient Alignment of Calcium Imaging Data through Simultaneous Low Rank and Sparse Decomposition. | Junmo Cho, Seungjae Han, Eun-Seo Cho, Kijung Shin, Young-Gyu Yoon |
| 2022 | AAAI | Meta-Learning for Online Update of Recommender Systems. | Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee |
| 2022 | CIKM | MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation. | Taeri Kim, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim |
| 2022 | CIKM | Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. | Geon Lee, Jaemin Yoo, Kijung Shin |
| 2022 | ICDE | Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications. | Shinhwan Kang, Kyuhan Lee, Kijung Shin |
| 2022 | ICDE | SLUGGER: Lossless Hierarchical Summarization of Massive Graphs. | Kyuhan Lee, Jihoon Ko, Kijung Shin |
| 2022 | ICDM | Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators. | Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin |
| 2022 | ICDM | Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data. | Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, Kijung Shin |
| 2022 | ICDM | Set2Box: Similarity Preserving Representation Learning for Sets. | Geon Lee, Chanyoung Park, Kijung Shin |
| 2022 | IJCAI | HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams. | Geon Lee, Minyoung Choe, Kijung Shin |
| 2022 | PAKDD | Are Edge Weights in Summary Graphs Useful? - A Comparative Study. | Shinhwan Kang, Kyuhan Lee, Kijung Shin |
| 2022 | WWW | MiDaS: Representative Sampling from Real-world Hypergraphs. | Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin |
| 2022 | SIGIR | AHP: Learning to Negative Sample for Hyperedge Prediction. | Hyunjin Hwang, Seungwoo Lee, Chanyoung Park, Kijung Shin |
| 2022 | WSDM | Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs. | Hyeonjeong Shin, Taehyung Kwon, Neil Shah, Kijung Shin |
| 2022 | WSDM | Directed Network Embedding with Virtual Negative Edges. | Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, Sang-Wook Kim |
| 2022 | SDM | On the Persistence of Higher-Order Interactions in Real-World Hypergraphs. | Hyunjin Choo, Kijung Shin |
| 2021 | AAAI | PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation. | Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee |
| 2021 | ICDE | SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams. | Taehyung Kwon, Inkyu Park, Dongjin Lee, Kijung Shin |
| 2021 | ICDE | Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers. | Dongjin Lee, Kijung Shin |
| 2021 | ICDM | THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting. | Geon Lee, Kijung Shin |
| 2021 | MICCAI | Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data. | Seungjae Han, Eun-Seo Cho, Inkyu Park, Kijung Shin, Young-Gyu Yoon |
| 2021 | WWW | How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators. | Geon Lee, Minyoung Choe, Kijung Shin |
| 2021 | SDM | DPGS: Degree-Preserving Graph Summarization. | Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng |
| 2020 | AAAI | Midas: Microcluster-Based Detector of Anomalies in Edge Streams. | Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos |
| 2020 | AAAI | TellTail: Fast Scoring and Detection of Dense Subgraphs. | Bryan Hooi, Kijung Shin, Hemank Lamba, Christos Faloutsos |
| 2020 | ICDM | Evolution of Real-world Hypergraphs: Patterns and Models without Oracles. | Yunbum Kook, Jihoon Ko, Kijung Shin |
| 2020 | KDD | Structural Patterns and Generative Models of Real-world Hypergraphs. | Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin |
| 2020 | KDD | Incremental Lossless Graph Summarization. | Jihoon Ko, Yunbum Kook, Kijung Shin |
| 2020 | KDD | SSumM: Sparse Summarization of Massive Graphs. | Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin |
| 2020 | WWW | How Much and When Do We Need Higher-order Informationin Hypergraphs? A Case Study on Hyperedge Prediction. | Se-eun Yoon, HyungSeok Song, Kijung Shin, Yung Yi |
| 2019 | KDD | Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. | Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos |
| 2019 | WWW | SWeG: Lossless and Lossy Summarization of Web-Scale Graphs. | Kijung Shin, Amol Ghoting, Myunghwan Kim, Hema Raghavan |
| 2019 | SDM | SMF: Drift-Aware Matrix Factorization with Seasonal Patterns. | Bryan Hooi, Kijung Shin, Shenghua Liu, Christos Faloutsos |
| 2018 | PAKDD | Tri-Fly: Distributed Estimation of Global and Local Triangle Counts in Graph Streams. | Kijung Shin, Mohammad Hammoud, Euiwoong Lee, Jinoh Oh, Christos Faloutsos |
| 2018 | WWW | Discovering Progression Stages in Trillion-Scale Behavior Logs. | Kijung Shin, Mahdi Shafiei, Myunghwan Kim, Aastha Jain, Hema Raghavan |
| 2017 | ICDM | WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams. | Kijung Shin |
| 2017 | IJCAI | Why You Should Charge Your Friends for Borrowing Your Stuff. | Kijung Shin, Euiwoong Lee, Dhivya Eswaran, Ariel D. Procaccia |
| 2017 | KDD | DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams. | Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos |
| 2017 | WSDM | S-HOT: Scalable High-Order Tucker Decomposition. | Jinoh Oh, Kijung Shin, Evangelos E. Papalexakis, Christos Faloutsos, Hwanjo Yu |
| 2017 | WSDM | D-Cube: Dense-Block Detection in Terabyte-Scale Tensors. | Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos |
| 2016 | ICDM | CoreScope: Graph Mining Using k-Core Analysis - Patterns, Anomalies and Algorithms. | Kijung Shin, Tina Eliassi-Rad, Christos Faloutsos |
| 2016 | KDD | FRAUDAR: Bounding Graph Fraud in the Face of Camouflage. | Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos |
| 2016 | WWW | Incorporating Side Information in Tensor Completion. | Hemank Lamba, Vaishnavh Nagarajan, Kijung Shin, Naji Shajarisales |
| 2015 | SIGMOD | BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs. | Kijung Shin, Jinhong Jung, Lee Sael, U Kang |
| 2014 | CIKM | Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression. | Dongyeop Kang, Woosang Lim, Kijung Shin, Lee Sael, U Kang |
| 2014 | ICDM | Distributed Methods for High-Dimensional and Large-Scale Tensor Factorization. | Kijung Shin, U Kang |