Faculty/Research

Research Groups

머신 인텔리전스 연구실

Machine Intelligence Lab.

Prof. : Prof. Jung, Kyomin

Research Area : Machine Learning, Big Data Analysis



  • About the Laboratory & Research Area
  • Machine Intelligence Lab (MILAB) at SNU focuses on learning essential structural properties of big data system, and designing scalable machine learning algorithms to analyze them. Currently our research topics include online social network trend classification, recommendation system, and complex network modeling and analysis. To that end, we are actively collaborating with world leading researchers in Microsoft Research, MIT, Bell Labs, and CUHK.
  • Research Interests & Projects
  • ▶ Research Interests:
    - Trend Prediction in Sequential Big Data
    - Recommendation System Design
    - Information Diffusion Analysis and Prediction in Social Networks
    - Scalable Learning Algorithms for Big Data
    - Statistical Inference in Graphical Models
    ▶ Projects:
    - Big Data Analysis for Social Networks (MEST)
    - Recommendation Systems for Smart Phones (LG Electronics)
  • Journals & Patents
  • [1] Yongsub Lim, Kyomin Jung and Pushmeet Kohli, “Efficient Energy Minimization for Enforcing Label Statistics”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2014.
    [2] Arnab Bhattacharyya, Elena Grigorescu, Kyomin Jung, Sofya Raskhodnikova and David Woodruff, “Transitive-Closure Spanners”, SIAM J. on Computing (SICOMP), 2012.
    [3] Arnab Bhattacharyya, Elena Grigorescu, Madhav Jha, Kyomin Jung, Sofya Raskhodnikova and David Woodruff, “Lower Bounds for Local Monotonicity Reconstruction from Transitive-Closure Spanners”, SIAM J. on Discrete Math (SIDMA), v.26, n.2, 618-646, 2012.
    [4] Kyomin Jung, Devavrat Shah and Jinwoo Shin, “Distributed Averaging Via Lifted Markov Chains”, IEEE Transactions on Information Theory, v.56, n.1, 634-647, 2010.
    [5] Sung-soon Choi, Kyomin Jung and Jeong Han Kim, “Almost Tight Upper Bound for Finding Fourier Coefficients of Bounded Pseudo-Boolean Functions”, Journal of Computer and System Sciences (JCSS), v.77, n.6, 1039-1053, 2011.
    [6] Sung-soon Choi, Kyomin Jung and Byung-Ro Moon, “Lower and Upper Bounds for Linkage Discovery”, IEEE Transactions on Evolutionary Computation, v.13,n.2, 201-216, 2009.
    [7] Sung-Soon Choi, Kyomin Jung and Jeong Han Kim, “Phase Transition in a Random NK Landscape Model”, Artificial Intelligence 172(2-3): 179-203, 2008.

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