PEGASUS: A Peta-Scale Graph Mining System. - U Kang; Charalampos E. Tsourakakis; Christos Faloutsos (ICDM, 2009)

DOULION: counting triangles in massive graphs with a coin. - Charalampos E. Tsourakakis; U Kang; Gary L. Miller; Christos Faloutsos (KDD, 2009)

Patterns on the Connected Components of Terabyte-Scale Graphs. - U Kang; Mary McGlohon; Leman Akoglu; Christos Faloutsos (ICDM, 2010)

Radius Plots for Mining Tera-byte Scale Graphs: Algorithms, Patterns, and Observations. - U Kang; Charalampos E. Tsourakakis; Ana Paula Appel; Christos Faloutsos; Jure Leskovec (SDM, 2010)

Mining large graphs: Algorithms, inference, and discoveries. - U Kang; Duen Horng Chau; Christos Faloutsos (ICDE, 2011)

Beyond 'Caveman Communities': Hubs and Spokes for Graph Compression and Mining. - U Kang; Christos Faloutsos (ICDM, 2011)

Clustering very large multi-dimensional datasets with MapReduce. - Robson Leonardo Ferreira Cordeiro; Caetano Traina Jr.; Agma Juci Machado Traina; Julio López 002; U Kang; Christos Faloutsos (KDD, 2011)

GBASE: a scalable and general graph management system. - U Kang; Hanghang Tong; Jimeng Sun 001; Ching-Yung Lin; Christos Faloutsos (KDD, 2011)

Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation. - U Kang; Brendan Meeder; Christos Faloutsos (PAKDD (2), 2011)

Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms. - Danai Koutra; Tai-You Ke; U Kang; Duen Horng Chau; Hsing-Kuo Kenneth Pao; Christos Faloutsos (ECML/PKDD (2), 2011)

Centralities in Large Networks: Algorithms and Observations. - U Kang; Spiros Papadimitriou; Jimeng Sun 001; Hanghang Tong (SDM, 2011)

PEGASUS: mining peta-scale graphs. - U Kang; Charalampos E. Tsourakakis; Christos Faloutsos (Knowl. Inf. Syst., 2011)

HADI: Mining Radii of Large Graphs. - U Kang; Charalampos E. Tsourakakis; Ana Paula Appel; Christos Faloutsos; Jure Leskovec (ACM Trans. Knowl. Discov. Data, 2011)

Pegasus: Mining billion-scale graphs in the cloud. - U Kang; Duen Horng Chau; Christos Faloutsos (ICASSP, 2012)

GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries. - U Kang; Evangelos E. Papalexakis; Abhay Harpale; Christos Faloutsos (KDD, 2012)

Fast Random Walk Graph Kernel. - U Kang; Hanghang Tong; Jimeng Sun 001 (SDM, 2012)

OPAvion: mining and visualization in large graphs. - Leman Akoglu; Duen Horng Chau; U Kang; Danai Koutra; Christos Faloutsos (SIGMOD Conference, 2012)

Managing and mining large graphs: patterns and algorithms. - Christos Faloutsos; U Kang (SIGMOD Conference, 2012)

Big graph mining: algorithms and discoveries. - U Kang; Christos Faloutsos (SIGKDD Explor., 2012)

gbase: an efficient analysis platform for large graphs. - U Kang; Hanghang Tong; Jimeng Sun 001; Ching-Yung Lin; Christos Faloutsos (VLDB J., 2012)

Mining Tera-Scale Graphs: Theory, Engineering and Discoveries. - U Kang (2012)

Big Data Clustering. - Hanghang Tong; U Kang (Data Clustering: Algorithms and Applications, 2013)

Leveraging memory mapping for fast and scalable graph computation on a PC. - Zhiyuan Lin 001; Duen Horng (Polo) Chau; U Kang (IEEE BigData, 2013)

Demonstrating Interactive Multi-resolution Large Graph Exploration. - Zhiyuan Lin 001; Nan Cao 001; Hanghang Tong; Fei Wang 001; U Kang; Duen Horng (Polo) Chau (ICDM Workshops, 2013)

Fast anomaly detection despite the duplicates. - Jay Yoon Lee; U Kang; Danai Koutra; Christos Faloutsos (WWW (Companion Volume), 2013)

Large Scale Tensor Decompositions: Algorithmic Developments and Applications. - Evangelos E. Papalexakis; U Kang; Christos Faloutsos; Nicholas D. Sidiropoulos; Abhay Harpale (IEEE Data Eng. Bull., 2013)

Fast and scalable approximate spectral graph matching for correspondence problems. - U Kang; Martial Hebert; Soonyong Park (Inf. Sci., 2013)

Mining Tera-Scale Graphs with "Pegasus": Algorithms and Discoveries. - U Kang; Christos Faloutsos (Large-Scale Data Analytics, 2014)

MMap: Fast billion-scale graph computation on a PC via memory mapping. - Zhiyuan Lin 001; Minsuk Kahng; Kaeser Md. Sabrin; Duen Horng (Polo) Chau; Ho Lee; U Kang (IEEE BigData, 2014)

Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression. - Dongyeop Kang; Woosang Lim; Kijung Shin; Lee Sael; U Kang (CIKM, 2014)

Fast, Accurate, and Space-efficient Tracking of Time-weighted Frequent Items from Data Streams. - Yongsub Lim; Jihoon Choi; U Kang (CIKM, 2014)

MapReduce Triangle Enumeration With Guarantees. - Ha-Myung Park; Francesco Silvestri 001; U Kang; Rasmus Pagh (CIKM, 2014)

Eventera: Real-Time Event Recommendation System from Massive Heterogeneous Online Media. - Dongyeop Kang; DongGyun Han; Nahea Park; Sangtae Kim; U Kang; Soobin Lee (ICDM Workshops, 2014)

Distributed Methods for High-Dimensional and Large-Scale Tensor Factorization. - Kijung Shin; U Kang (ICDM, 2014)

Net-Ray: Visualizing and Mining Billion-Scale Graphs. - U Kang; Jay Yoon Lee; Danai Koutra; Christos Faloutsos (PAKDD (1), 2014)

VOG: Summarizing and Understanding Large Graphs. - Danai Koutra; U Kang; Jilles Vreeken; Christos Faloutsos (SDM, 2014)

Big graph mining for the web and social media: algorithms, anomaly detection, and applications. - U Kang; Leman Akoglu; Duen Horng Chau (WSDM, 2014)

Link prediction based on generalized cluster information. - Jungeun Kim; Minsoo Choy; Daehoon Kim; U Kang (WWW (Companion Volume), 2014)

HEigen: Spectral Analysis for Billion-Scale Graphs. - U Kang; Brendan Meeder; Evangelos E. Papalexakis; Christos Faloutsos (IEEE Trans. Knowl. Data Eng., 2014)

SlashBurn: Graph Compression and Mining beyond Caveman Communities. - Yongsub Lim; U Kang; Christos Faloutsos (IEEE Trans. Knowl. Data Eng., 2014)

An extension of the automatic cross-association method with a 3-dimensional matrix. - Won-Jo Lee; Chae-Gyun Lim; U Kang; Ho-Jin Choi (BigComp, 2015)

Discovering large subsets with high quality partitions in real world graphs. - Yongsub Lim; Won-Jo Lee; Ho-Jin Choi; U Kang (BigComp, 2015)

HaTen2: Billion-scale tensor decompositions. - Inah Jeon; Evangelos E. Papalexakis; U Kang; Christos Faloutsos (ICDE, 2015)

TeGViz: Distributed Tera-Scale Graph Generation and Visualization. - Byungsoo Jeon; Inah Jeon; U Kang (ICDM Workshops, 2015)

MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams. - Yongsub Lim; U Kang (KDD, 2015)

BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs. - Kijung Shin; Jinhong Jung; Lee Sael; U Kang (SIGMOD Conference, 2015)

Scalable Tensor Mining. - Lee Sael; Inah Jeon; U Kang (Big Data Res., 2015)

M-Flash: Fast Billion-scale Graph Computation Using Block Partition Model. - Hugo Gualdron; Robson L. F. Cordeiro; José Fernando Rodrigues Jr.; Duen Horng Chau; Minsuk Kahng; U Kang (CoRR, 2015)

Reverse nearest neighbor search with a non-spatial aspect. - Jeong-Hoon Park; Chin-Wan Chung; U Kang (Inf. Syst., 2015)

Fast graph mining with HBase. - Ho Lee; Bin Shao; U Kang (Inf. Sci., 2015)

Summarizing and understanding large graphs. - Danai Koutra; U Kang; Jilles Vreeken; Christos Faloutsos (Stat. Anal. Data Min., 2015)

PIN-TRUST: Fast Trust Propagation Exploiting Positive, Implicit, and Negative Information. - Min-Hee Jang; Christos Faloutsos; Sang-Wook Kim; U Kang; Jiwoon Ha (CIKM, 2016)

BIGtensor: Mining Billion-Scale Tensor Made Easy. - Namyong Park; Byungsoo Jeon; Jungwoo Lee; U Kang (CIKM, 2016)

SCouT: Scalable coupled matrix-tensor factorization - algorithm and discoveries. - Byungsoo Jeon; Inah Jeon; Lee Sael; U Kang (ICDE, 2016)

Personalized Ranking in Signed Networks Using Signed Random Walk with Restart. - Jinhong Jung; Woojeong Jin 001; Lee Sael; U Kang (ICDM, 2016)

Partition Aware Connected Component Computation in Distributed Systems. - Ha-Myung Park; Namyong Park; Sung-Hyon Myaeng; U Kang (ICDM, 2016)

PTE: Enumerating Trillion Triangles On Distributed Systems. - Ha-Myung Park; Sung-Hyon Myaeng; U Kang (KDD, 2016)

M-Flash: Fast Billion-Scale Graph Computation Using a Bimodal Block Processing Model. - Hugo Gualdron; Robson L. F. Cordeiro; José Fernando Rodrigues Jr.; Duen Horng (Polo) Chau; Minsuk Kahng; U Kang (ECML/PKDD (2), 2016)

FURL: Fixed-memory and Uncertainty Reducing Local Triangle Counting for Graph Streams. - Minsoo Jung; Sunmin Lee; Yongsub Lim; U Kang (CoRR, 2016)

Random Walk with Restart on Large Graphs Using Block Elimination. - Jinhong Jung; Kijung Shin; Lee Sael; U Kang (ACM Trans. Database Syst., 2016)

Mining billion-scale tensors: algorithms and discoveries. - Inah Jeon; Evangelos E. Papalexakis; Christos Faloutsos; Lee Sael; U Kang (VLDB J., 2016)

A comparative study of matrix factorization and random walk with restart in recommender systems. - Haekyu Park; Jinhong Jung; U Kang (IEEE BigData, 2017)

A New Question Answering Approach with Conceptual Graphs. - Kyung-Min Kim; Jinhong Jung; Jihee Ryu; Ha-Myung Park; Joseph P. Joohee; Seokwoo Jeong; U Kang; Sung-Hyon Myaeng (CORIA, 2017)

Fast and Scalable Distributed Boolean Tensor Factorization. - Namyong Park; Sejoon Oh; U Kang (ICDE, 2017)

Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks. - Jaemin Yoo; Saehan Jo; U Kang (ICDM, 2017)

BePI: Fast and Memory-Efficient Method for Billion-Scale Random Walk with Restart. - Jinhong Jung; Namyong Park; Lee Sael; U Kang (SIGMOD Conference, 2017)

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

Fast, Accurate, and Scalable Method for Sparse Coupled Matrix-Tensor Factorization. - Dongjin Choi; Jun-Gi Jang; 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)

Supervised and Extended Restart in Random Walks for Ranking and Link Prediction in Networks. - Woojeong Jin 001; Jinhong Jung; U Kang (CoRR, 2017)

UniWalk: Explainable and Accurate Recommendation for Rating and Network Data. - Haekyu Park; Hyunsik Jeon; Junghwan Kim; Beunguk Ahn; U Kang (CoRR, 2017)

Time-weighted counting for recently frequent pattern mining in data streams. - Yongsub Lim; U Kang (Knowl. Inf. Syst., 2017)

Fully Scalable Methods for Distributed Tensor Factorization. - Kijung Shin; Lee Sael; U Kang (IEEE Trans. Knowl. Data Eng., 2017)

MTP: discovering high quality partitions in real world graphs. - Yongsub Lim; Won-Jo Lee; Ho-Jin Choi; U Kang (World Wide Web, 2017)

PegasusN: A Scalable and Versatile Graph Mining System. - Ha-Myung Park; Chiwan Park; U Kang (AAAI, 2018)

Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Patterns in an Arbitrary Time Range. - Jun-Gi Jang; Dongjin Choi; Jinhong Jung; U Kang (CIKM, 2018)

Scalable Tucker Factorization for Sparse Tensors - Algorithms and Discoveries. - Sejoon Oh; Namyong Park; Lee Sael; U Kang (ICDE, 2018)

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 Scalable Distributed Loopy Belief Propagation on Real-World Graphs. - Saehan Jo; Jaemin Yoo; U Kang (WSDM, 2018)

SIDE: Representation Learning in Signed Directed Networks. - Junghwan Kim; Haekyu Park; Ji-Eun Lee; U Kang (WWW, 2018)

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

TR-SVD: Fast and Memory Efficient Method for Time Ranged Singular Value Decomposition. - Jun-Gi Jang; Dongjin Choi; Jinhong Jung; U Kang (CoRR, 2018)

Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets. - Mauro Scanagatta; Giorgio Corani; Marco Zaffalon; Jaemin Yoo; U Kang (Int. J. Approx. Reason., 2018)

Memory-Efficient and Accurate Sampling for Counting Local Triangles in Graph Streams: From Simple to Multigraphs. - Yongsub Lim; Minsoo Jung; U Kang (ACM Trans. Knowl. Discov. Data, 2018)

Enumerating Trillion Subgraphs On Distributed Systems. - Ha-Myung Park; Francesco Silvestri 001; Rasmus Pagh; Chin-Wan Chung; Sung-Hyon Myaeng; U Kang (ACM Trans. Knowl. Discov. Data, 2018)

Data Context Adaptation for Accurate Recommendation with Additional Information. - Hyunsik Jeon; Bonhun Koo; U Kang (IEEE BigData, 2019)

Belief Propagation Network for Hard Inductive Semi-Supervised Learning. - Jaemin Yoo; Hyunsik Jeon; U Kang (IJCAI, 2019)

Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance. - Seungcheol Park; Shuyu Wang; Hunjung Lim; U Kang (IROS, 2019)

Knowledge Extraction with No Observable Data. - Jaemin Yoo; Minyong Cho; Taebum Kim; U Kang (NeurIPS, 2019)

PS-MCL: parallel shotgun coarsened Markov clustering of protein interaction networks. - Yongsub Lim; In-Jae Yu; Dongmin Seo; U Kang; Lee Sael (BMC Bioinform., 2019)

FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN. - Chun Quan; Jun-Gi Jang; Hyun Dong Lee; U Kang (CoRR, 2019)

How to Pick the Best Source Data? Measuring Transferability for Heterogeneous Domains. - Seungcheol Park; Huiwen Xu; Taehun Kim; Inhwan Hwang; Kyung-Jun Kim; U Kang (CoRR, 2019)

FURL: Fixed-memory and uncertainty reducing local triangle counting for multigraph streams. - Minsoo Jung; Yongsub Lim; Sunmin Lee; U Kang (Data Min. Knowl. Discov., 2019)

High-Performance Tucker Factorization on Heterogeneous Platforms. - Sejoon Oh; Namyong Park; Jun-Gi Jang; Lee Sael; U Kang (IEEE Trans. Parallel Distributed Syst., 2019)

Fast and scalable method for distributed Boolean tensor factorization. - Namyong Park; Sejoon Oh; U Kang (VLDB J., 2019)

Gtensor: Fast and Accurate Tensor Analysis System using GPUs. - Dawon Ahn; Sangjun Son; U Kang (CIKM, 2020)

BalanSiNG: Fast and Scalable Generation of Realistic Signed Networks. - Jinhong Jung; Ha-Myung Park; U Kang (EDBT, 2020)

D-Tucker: Fast and Memory-Efficient Tucker Decomposition for Dense Tensors. - Jun-Gi Jang; U Kang (ICDE, 2020)

Accurate News Recommendation Coalescing Personal and Global Temporal Preferences. - Bonhun Koo; Hyunsik Jeon; U Kang (PAKDD (1), 2020)

Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference. - Jaemin Yoo; U Kang; Mauro Scanagatta; Giorgio Corani; Marco Zaffalon (WSDM, 2020)

Fast Partial Fourier Transform. - Yong-chan Park; Jun-Gi Jang; U Kang (CoRR, 2020)

Ensemble Multi-Source Domain Adaptation with Pseudolabels. - Seongmin Lee 006; Hyunsik Jeon; U Kang (CoRR, 2020)

AUBER: Automated BERT Regularization. - Hyun Dong Lee; Seongmin Lee 006; U Kang (CoRR, 2020)

Pea-KD: Parameter-efficient and Accurate Knowledge Distillation. - Ikhyun Cho; U Kang (CoRR, 2020)

Time-Aware Tensor Decomposition for Missing Entry Prediction. - Dawon Ahn; Jun-Gi Jang; U Kang (CoRR, 2020)

T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion. - Jaehun Jung; Jinhong Jung; U Kang (CoRR, 2020)

Signed Graph Diffusion Network. - Jinhong Jung; Jaemin Yoo; U Kang (CoRR, 2020)

Random walk-based ranking in signed social networks: model and algorithms. - Jinhong Jung; Woojeong Jin 001; U Kang (Knowl. Inf. Syst., 2020)

Accurate Online Tensor Factorization for Temporal Tensor Streams with Missing Values. - Dawon Ahn; Seyun Kim; U Kang (CIKM, 2021)

Accurate Graph-Based PU Learning without Class Prior. - Jaemin Yoo; Junghun Kim; Hoyoung Yoon; Geonsoo Kim; Changwon Jang; U Kang (ICDM, 2021)

Fast and Memory-Efficient Tucker Decomposition for Answering Diverse Time Range Queries. - Jun-Gi Jang; U Kang (KDD, 2021)

Learning to Walk across Time for Interpretable Temporal Knowledge Graph Completion. - Jaehun Jung; Jinhong Jung; U Kang (KDD, 2021)

Fast and Accurate Partial Fourier Transform for Time Series Data. - Yong-chan Park; Jun-Gi Jang; U Kang (KDD, 2021)

Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts. - Jaemin Yoo; Yejun Soun; Yong-chan Park; U Kang (KDD, 2021)

Attention-Based Autoregression for Accurate and Efficient Multivariate Time Series Forecasting. - Jaemin Yoo; U Kang (SDM, 2021)

PGT: news recommendation coalescing personal and global temporal preferences. - Bonhun Koo; Hyunsik Jeon; U Kang (Knowl. Inf. Syst., 2021)

Transfer alignment network for blind unsupervised domain adaptation. - Huiwen Xu; U Kang (Knowl. Inf. Syst., 2021)

Accurate relational reasoning in edge-labeled graphs by multi-labeled random walk with restart. - Jinhong Jung; Woojeong Jin 001; Ha-Myung Park; U Kang (World Wide Web, 2021)

Accurate PARAFAC2 Decomposition for Temporal Irregular Tensors with Missing Values. - Jun-Gi Jang; Jeongyoung Lee; Jiwon Park; U Kang (IEEE Big Data, 2022)

Accurate Stock Movement Prediction with Self-supervised Learning from Sparse Noisy Tweets. - Yejun Soun; Jaemin Yoo; Minyong Cho; Jihyeong Jeon; U Kang (IEEE Big Data, 2022)

Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledge. - Hyunsik Jeon; Jongjin Kim 001; Hoyoung Yoon; Jaeri Lee; U Kang (CIKM, 2022)

DPar2: Fast and Scalable PARAFAC2 Decomposition for Irregular Dense Tensors. - Jun-Gi Jang; U Kang (ICDE, 2022)

Accurate Node Feature Estimation with Structured Variational Graph Autoencoder. - Jaemin Yoo; Hyunsik Jeon; Jinhong Jung; U Kang (KDD, 2022)

MiDaS: Representative Sampling from Real-world Hypergraphs. - Minyoung Choe; Jaemin Yoo; Geon Lee; Woonsung Baek; U Kang; Kijung Shin (WWW, 2022)

Model-Agnostic Augmentation for Accurate Graph Classification. - Jaemin Yoo; Sooyeon Shim; U Kang (WWW, 2022)

Accurate Bundle Matching and Generation via Multitask Learning with Partially Shared Parameters. - Hyunsik Jeon; Jun-Gi Jang; Taehun Kim; U Kang (CoRR, 2022)

Graph-based PU learning for binary and multiclass classification without class prior. - Jaemin Yoo; Junghun Kim; Hoyoung Yoon; Geonsoo Kim; Changwon Jang; U Kang (Knowl. Inf. Syst., 2022)

Time-aware tensor decomposition for sparse tensors. - Dawon Ahn; Jun-Gi Jang; U Kang (Mach. Learn., 2022)

Finding Key Structures in MMORPG Graph with Hierarchical Graph Summarization. - Jun-Gi Jang; Chaeheum Park; Changwon Jang; Geonsoo Kim; U Kang (ACM Trans. Knowl. Discov. Data, 2022)

Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance. - Huiwen Xu; U Kang (ICCV, 2023)

Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors - Algorithm and Application. - Jun-Gi Jang; Jeongyoung Lee; Yong-chan Park; U Kang (KDD, 2023)

Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-Aware Reranking. - Hyunsik Jeon; Jongjin Kim 001; Jaeri Lee; Jong-eun Lee; U Kang (PAKDD (3), 2023)

Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation. - Jongjin Kim 001; Hyunsik Jeon; Jaeri Lee; U Kang (PAKDD (3), 2023)

Knowledge-preserving Pruning for Pre-trained Language Models without Retraining. - Seungcheol Park; Hojun Choi; U Kang (CoRR, 2023)

Accurate Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating. - Hyunsik Jeon; Jong-eun Lee; Jeongin Yun; U Kang (CoRR, 2023)

Falcon: lightweight and accurate convolution based on depthwise separable convolution. - Jun-Gi Jang; Chun Quan; Hyun Dong Lee; U Kang (Knowl. Inf. Syst., 2023)

Static and Streaming Tucker Decomposition for Dense Tensors. - Jun-Gi Jang; U Kang (ACM Trans. Knowl. Discov. Data, 2023)

Accurate Open-Set Recognition for Memory Workload. - Jun-Gi Jang; Sooyeon Shim; Vladimir Egay; Jeeyong Lee; Jongmin Park; Suhyun Chae; U Kang (ACM Trans. Knowl. Discov. Data, 2023)

Accurate Stock Movement Prediction via Multi-Scale and Multi-Domain Modeling. - JinGee Kim; Yong-chan Park; Jaemin Hong; U Kang (IEEE Big Data, 2024)

Accurate Coupled Tensor Factorization with Knowledge Graph. - SeungJoo Lee; Yong-chan Park; U Kang (IEEE Big Data, 2024)

Towards True Multi-interest Recommendation: Enhanced Scheme for Balanced Interest Training. - Jaeri Lee; Jeongin Yun; U Kang (IEEE Big Data, 2024)

Fast and Accurate PARAFAC2 Decomposition for Time Range Queries on Irregular Tensors. - Jun-Gi Jang; Yong-chan Park; U Kang (CIKM, 2024)

Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models. - Seungcheol Park; Hojun Choi; U Kang (ICLR, 2024)

Domain-Aware Data Selection for Speech Classification via Meta-Reweighting. - Junghun Kim; Ka Hyun Park; Hoyoung Yoon; U Kang (INTERSPEECH, 2024)

FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition. - Jihyeong Jeon; Jiwon Park; Chanhee Park; U Kang (KDD, 2024)

Fast and Accurate Domain Adaptation for Irregular Tensor Decomposition. - Junghun Kim; Ka Hyun Park; Jun-Gi Jang; U Kang (KDD, 2024)

Fast Multidimensional Partial Fourier Transform with Automatic Hyperparameter Selection. - Yong-chan Park; Jongjin Kim 001; U Kang (KDD, 2024)

Accurate Semi-supervised Automatic Speech Recognition via Multi-hypotheses-Based Curriculum Learning. - Junghun Kim; Ka Hyun Park; U Kang (PAKDD (5), 2024)

Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating. - Hyunsik Jeon; Jong-eun Lee; Jeongin Yun; U Kang (WWW, 2024)

DDC3N: Doppler-Driven Convolutional 3D Network for Human Action Recognition. - Toshpulatov Mukhiddin; Wookey Lee; Suan Lee; Hoyoung Yoon; U Kang (IEEE Access, 2024)

A Comprehensive Survey of Compression Algorithms for Language Models. - Seungcheol Park; Jaehyeon Choi; Sojin Lee; U Kang (CoRR, 2024)

PULL: PU-Learning-based Accurate Link Prediction. - Junghun Kim; Ka Hyun Park; Hoyoung Yoon; U Kang (CoRR, 2024)

Representative and Back-In-Time Sampling from Real-world Hypergraphs. - Minyoung Choe; Jaemin Yoo; Geon Lee; Woonsung Baek; U Kang; Kijung Shin (ACM Trans. Knowl. Discov. Data, 2024)

Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning. - Junghun Kim; Ka Hyun Park; Hoyoung Yoon; U Kang (AAAI, 2025)

Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models. - Seungcheol Park; Jeongin Bae; Beomseok Kwon; Minjun Kim 010; Byeongwook Kim; Se Jung Kwon; U Kang; Dongsoo Lee (ACL (1), 2025)

SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning. - Minjun Kim 010; Jongjin Kim 001; U Kang (ICLR, 2025)

AugWard: Augmentation-Aware Representation Learning for Accurate Graph Classification. - Minjun Kim 010; Jaehyeon Choi; SeungJoo Lee; Jinhong Jung; U Kang (PAKDD (2), 2025)

DART: Diversified and Accurate Long-Tail Recommendation. - Jeongin Yun; Jaeri Lee; U Kang (PAKDD (3), 2025)

Sequentially Diversified and Accurate Recommendations in Chronological Order for a Series of Users. - Jongjin Kim 001; U Kang (WSDM, 2025)

Zero-shot Quantization: A Comprehensive Survey. - Minjun Kim 010; Jaehyeon Choi; Jongkeun Lee; Wonjin Cho; U Kang (CoRR, 2025)

Accurate Sublayer Pruning for Large Language Models by Exploiting Latency and Tunability Information. - Seungcheol Park; Sojin Lee; Jongjin Kim 001; Jinsik Lee; Hyunjik Jo; U Kang (CoRR, 2025)