Join processing using Bloom filter in MapReduce. - Taewhi Lee; Kisung Kim; Hyoung-Joo Kim 001 (RACS, 2012)

A parallel tag affinity computation for social tagging systems using MapReduce. - Hyunwoo Kim; Taewhi Lee; Hyoung-Joo Kim 001 (Int. J. Big Data Intell., 2014)

Join processing with threshold-based filtering in MapReduce. - Taewhi Lee; Hye-Chan Bae; Hyoung-Joo Kim 001 (J. Supercomput., 2014)

Flying KIWI: Design of Approximate Query Processing Engine for Interactive Data Analytics at Scale. - Sung-Soo Kim; Taewhi Lee; Moonyoung Chung; Jongho Won (BigDAS, 2015)

Sweet KIWI: Statistics-Driven OLAP Acceleration using Query Column Sets. - Sung-Soo Kim; Taewhi Lee; Moonyoung Chung; Jongho Won (EDBT, 2016)

Parallel Prime Number Labeling of Large XML Data Using MapReduce. - Jinhyun Ahn; Dong-Hyuk Im; Taewhi Lee; Hong-Gee Kim (ICITCS, 2016)

Partial Materialization for Data Integration in SQL-on-Hadoop Engines. - Taewhi Lee; Moonyoung Chung; Sung-Soo Kim; Hyewon Song; Jongho Won (ICITCS, 2016)

A dynamic and parallel approach for repetitive prime labeling of XML with MapReduce. - Jinhyun Ahn; Dong-Hyuk Im; Taewhi Lee; Hong-Gee Kim (J. Supercomput., 2017)

Enhancing Prediction of Chlorophyll-a Concentration with Feature Extraction using Higher-Order Partial Least Squares. - Taewhi Lee; Jang-Ho Choi; Miyoung Jang; Jongho Won; Jiyong Kim (ICTC, 2020)

Exploiting Machine Learning Models for Approximate Query Processing. - Taewhi Lee; Kihyuk Nam; Choon Seo Park; Sung-Soo Kim (IEEE Big Data, 2022)

An Efficient Data Analysis For Edge-Enabled Distributed Environments using Tractable Probabilistic Models. - Kihyuk Nam; Taewhi Lee; Sung-Soo Kim; Choon Seo Park; Taek Yong Nam; Insik Shin (IEEE Big Data, 2022)

Exploiting Heterogeneous Monitoring Data for Spatiotemporal Algal Bloom Prediction. - Taewhi Lee; Miyoung Jang; Jang-Ho Choi; Jongho Won; Jiyong Kim (ICAIIC, 2022)

Designing ML-based Approximate Query Processing Services on Time-Varying Large Dataset for Distributed Systems. - Kihyuk Nam; Sung-Soo Kim; Choon Seo Park; Taek Yong Nam; Taewhi Lee (ICTC, 2022)

TCAC-GAN: Synthetic Trajectory Generation Model Using Auxiliary Classifier Generative Adversarial Networks for Improved Protection of Trajectory Data. - Jihwan Shin; Yeji Song; Jinhyun Ahn; Taewhi Lee; Dong-Hyuk Im (BigComp, 2023)

Learning for Spatio-temporal and Relational Data. - Kihyuk Nam; Taewhi Lee; Sung-Soo Kim; Insik Shin (IEEE Big Data, 2023)

Privacy-preserving Approximate Query Processing with Differentially Private Generative Models. - Jiwon Ock; Taewhi Lee; Seongmin Kim (IEEE Big Data, 2023)

Except-Condition Generative Adversarial Network for Generating Trajectory Data. - Yeji Song; Jihwan Shin; Jinhyun Ahn; Taewhi Lee; Dong-Hyuk Im (DEXA (2), 2023)

Towards Better Time-series Data Augmentation for Contrastive Learning. - Jang-Ho Choi; Moonyoung Chung; Taewhi Lee; Jiyong Kim (ICTC, 2023)

A Framework for Learned Approximate Query Processing for Tabular Data with Trajectory. - Kihyuk Nam; Sung-Soo Kim; Choon Seo Park; Taek Yong Nam; Taewhi Lee (ICTC, 2023)

TK-BERT: Effective Model of Language Representation using Topic-based Knowledge Graphs. - Chanwook Min; Jinhyun Ahn; Taewhi Lee; Dong-Hyuk Im (IMCOM, 2023)

Generating Labeled Multiple Attribute Trajectory Data With Selective Partial Anonymization Based on Exceptional Conditional Generative Adversarial Network. - Yeji Song; Jihwan Shin; Jinhyun Ahn; Taewhi Lee; Dong-Hyuk Im (IEEE Access, 2023)

Constrained Approximate Query Processing with Error and Response Time-Bound Guarantees for Efficient Big Data Analytics. - Sungsoo Kim; Choon Seo Park; Taewhi Lee; Kihyuk Nam (HPDC, 2024)

Advanced Trajectory Privacy Protection with Attention Mechanism and Auxiliary Classifier Generative Adversarial Networks. - Jihwan Shin; Yeji Song; Yoo-Young Cheong; Jinhyun Ahn; Taewhi Lee; Dong-Hyuk Im (ICOIN, 2024)

Differential privacy in statistical queries for synthetic trajectories generated by generative adversarial networks. - Jihwan Shin; Yeji Song; Minsoo Jang; Jinhyun Ahn; Taewhi Lee; Dong-Hyuk Im (Connect. Sci., 2025)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)