/ Yongsub Lim


  1. Yongsub Lim, Injae Yu, Dongmin Seo, U Kang, and Lee Sael
    PS-MCL: Parallel shotgun coarsened Markov clustering of protein interaction networks
    BMC Bioinformatics, 2019
    [pdf] [bib]
  2. Minsoo Jung, Yongsub Lim, Sumin Lee, and U Kang
    FURL: Fixed-memory and uncertainty reducing local triangle counting for multigraph streams
    Data Mining and Knowledge Discovery (DMKD), 2019
    [pdf] [bib] [publisher’s link]
  3. Yongsub Lim, Minsoo Jung, and U Kang
    Memory-efficient and accurate sampling for counting local triangles in graph streams: from simple to multigraphs
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2018
    [pdf] [bib]
  4. Andre S. Yoon, Taehoon Lee, Yongsub Lim, Deokwoo Jung, Philgyun Kang, Dongwon Kim, Keuntae Park, and Yongjin Choi
    Semi-supervised learning with deep generative models for asset failure prediction
    2nd ACM SIGKDD Workshop on Machine Learning for Prognostics and Health Management (ML for PHM), 2017
    [pdf] [bib]
  5. Yongsub Lim, and U Kang
    Time-weighted counting for recently frequent pattern mining in data streams
    Knowledge and Information Systems (KAIS), 2017
    [pdf] [bib]
  6. Woosang Lim, Jungsoo Lee, Yongsub Lim, Doo-Hwan Bae, Haesun Park, Dae-Shik Kim, and Kyomin Jung
    Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets
    PLoS ONE, 2017
    [pdf] [bib]
  7. Heeyoung Kwak, Joonyoung Kim, Yongsub Lim, Shin-Kap Han, and Kyomin Jung
    Centrality fairness: Measuring and analyzing structural inequality of online social network
    Journal of Internet Technology (JIT), 2017
    [pdf] [bib]
  8. Yongsub Lim, Won-Jo Lee, Ho-Jin Choi, and U Kang
    MTP: Discovering high quality partitions in real world graphs
    World Wide Web Journal, 2016
    [pdf] [bib]
  9. Yongsub Lim, and U Kang
    MASCOT: Memory-efficient and accurate sampling for counting local triangles in graph streams
    21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015
    [pdf] [bib]
  10. Adrian Kim, Kyomin Jung, Yongsub Lim, Daniel Tarlow, and Pushmeet Kohli
    Minimizing expected losses in perturbation models with multidimensional parametric min-cuts*
    31st Conference on Uncertainty in Artificial Intelligence (UAI), 2015
    [pdf] [bib]
  11. Yongsub Lim*, Won-Jo Lee*, Ho-Jin Choi, and U Kang
    Discovering large subsets with high quality partitions in real world graphs
    Second International Conference on Big Data and Smart Computing (BigComp), 2015
    (*These authors contributed equally to this work)
    [pdf] [bib]
  12. Yongsub Lim, Jihoon Choi, and U Kang
    Fast, accurate, and space-efficient tracking of time-weighted frequent items from data streams
    23rd ACM International Conference on Information and Knowledge Management (CIKM), 2014
    [pdf] [bib]
  13. Yongsub Lim, U Kang, and Christos Faloutsos
    SlashBurn: Graph compression and mining beyond caveman communities
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2014
    [pdf] [bib]
  14. Yongsub Lim, Kyomin Jung, and Pushmeet Kohli
    Efficient energy minimization for enforcing label statistics
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014
    [pdf] [bib]
  15. Yongsub Lim, and Kyomin Jung
    Decentralized control for intelligent robot system to avoid moving obstacles
    Fourth International Conference on Intelligent Systems, Modelling and Simulation (ISMS), 2013
    [pdf] [bib]
  16. Yongsub Lim, Kyomin Jung, and Pushmeet Kohli
    Constrained discrete optimization via dual space search
    NIPS Workshop on Discrete Optimization in Machine Learning 2011: Uncertainty, Generalization and Feedback (DISCML), 2011
    [pdf] [bib]
  17. Yongsub Lim, Kyomin Jung, and Pushmeet Kohli
    Energy minimization under constraints on label counts
    The 11th European Conference on Computer Vision (ECCV), 2010
    [pdf] [bib] [supp]