Slashburn: Graph compression and mining beyond caveman communities Y Lim, U Kang, C Faloutsos IEEE Transactions on Knowledge and Data Engineering 26 (12), 3077-3089, 2014 | 180 | 2014 |
Mascot: Memory-efficient and accurate sampling for counting local triangles in graph streams Y Lim, U Kang Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 116 | 2015 |
Rapp: Novelty detection with reconstruction along projection pathway KH Kim, S Shim, Y Lim, J Jeon, J Choi, B Kim, AS Yoon International Conference on Learning Representations, 2019 | 87 | 2019 |
Semi-supervised learning with deep generative models for asset failure prediction AS Yoon, T Lee, Y Lim, D Jung, P Kang, D Kim, K Park, Y Choi arXiv preprint arXiv:1709.00845, 2017 | 75 | 2017 |
Memory-efficient and accurate sampling for counting local triangles in graph streams: from simple to multigraphs Y Lim, M Jung, U Kang ACM Transactions on Knowledge Discovery from Data (TKDD) 12 (1), 1-28, 2018 | 34 | 2018 |
Anomaly detection AS Yoon, LIM Yongsub, S Shim US Patent 10,803,384, 2020 | 33 | 2020 |
Energy minimization under constraints on label counts Y Lim, K Jung, P Kohli Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 31 | 2010 |
Time-weighted counting for recently frequent pattern mining in data streams Y Lim, U Kang Knowledge and Information Systems 53, 391-422, 2017 | 19 | 2017 |
FURL: Fixed-memory and uncertainty reducing local triangle counting for multigraph streams M Jung, Y Lim, S Lee, U Kang Data Mining and Knowledge Discovery 33, 1225-1253, 2019 | 16 | 2019 |
Discovering large subsets with high quality partitions in real world graphs Y Lim, WJ Lee, HJ Choi, U Kang 2015 International Conference on Big Data and Smart Computing (BIGCOMP), 186-193, 2015 | 16 | 2015 |
Efficient energy minimization for enforcing label statistics Y Lim, K Jung, P Kohli IEEE transactions on pattern analysis and machine intelligence 36 (9), 1893-1899, 2014 | 14 | 2014 |
PS-MCL: parallel shotgun coarsened Markov clustering of protein interaction networks Y Lim, I Yu, D Seo, U Kang, L Sael BMC bioinformatics 20, 1-12, 2019 | 12 | 2019 |
MTP: discovering high quality partitions in real world graphs Y Lim, WJ Lee, HJ Choi, U Kang World Wide Web 20, 491-514, 2017 | 12 | 2017 |
Fast, accurate, and space-efficient tracking of time-weighted frequent items from data streams Y Lim, J Choi, U Kang Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 11 | 2014 |
Semi-supervised learning with deep generative models for asset failure prediction. arXiv AS Yoon, T Lee, Y Lim, D Jung, P Kang, D Kim, Y Choi arXiv preprint arXiv:1709.00845, 2017 | 6 | 2017 |
Anomaly detection AS Yoon, S Shim, LIM Yongsub, KH Kim, KIM Byungchan US Patent 11,537,900, 2022 | 5 | 2022 |
Novelty detection using deep learning neural network AS Yoon, S Shim, LIM Yongsub, KH Kim, KIM Byungchan, J Choi, J Jeon US Patent 11,301,756, 2022 | 5 | 2022 |
FURL: fixed-memory and uncertainty reducing local triangle counting for graph streams M Jung, S Lee, Y Lim, U Kang arXiv preprint arXiv:1611.06615, 2016 | 5 | 2016 |
Constrained discrete optimization via dual space search Y Lim, J Kyomin, P Kohli NIPS Workshop on Discrete Optimization on Machine Learning, 2011 | 4 | 2011 |
Multi-dimensional parametric mincuts for constrained map inference Y Lim, K Jung, P Kohli arXiv preprint arXiv:1307.7793, 2013 | 3 | 2013 |