Hauptnavigation

IMG_2529-001.JPG Email: sangkyun.lee cs.uni-dortmund.de
Phone: 0231/755-6490
Fax: 0231/755-5105
Room-No.: OH12 R4.023

About

I'm interested in developing efficient numerical optimization algorithms for statistical data analyses, focusing on online non-smooth convex regularization problems.

I received my Ph.D. degree (major in optimization, minor in statistics) from the Computer Sciences Department of the University of Wisconsin-Madison, in 2011. From the same university I obtained my second master's degree in Computer Science, in 2008. I was born in South Korea, and before coming to the USA I studied in Seoul National University and received my bachelor's (summa cum laude) and my first master's degree (artificial intelligence/bioinformatics) in Computer Sciences and Engineering, in 2003 and 2005, respectively. I'm working in the Collaborative Research Center (SFB876) at TU Dortmund since August, 2011, as a postdoc researcher.
My website at University of Wisconsin-Madison link

Lectures

  • Numerical Optimization SoSe 2014 link

Projects

Research Topics

Publications

Lee/2014a Lee, Sangkyun. Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure. In Holzinger, Andreas and Jurisica, Igor (editors), Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, Vol. 8401, pages 227--240, Springer, 2014.
Lee/2014b Lee, Sangkyun. Characterization of Subgroup Patterns from Graphical Representation of Genomic Data. In \'Sl\c ezak, Dominik and Tan, Ah-Hwee and Peters, JamesF. and Schwabe, Lars (editors), Brain Informatics and Health, Vol. 8609, pages 516--527, Springer, 2014.
Lee/Poelitz/2014a Lee, Sangkyun and Pölitz, Christian. Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-Limited Sensor Networks. In International Conference on Pattern Recognition Applications and Methods, 2014.
Lee/Poelitz/2014b Sangkyun Lee and Christian P\"olitz. Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines. In Maria De Marsico and Antoine Tabbone and Ana Fred (editors), ICPRAM 2014 - Best Papers, Vol. (to appear), 2014.
Piatkowski/etal/2014a Piatkowski, Nico and Sangkyun, Lee and Morik,Katharina. The Integer Approximation of Undirected Graphical Models. In De Marsico, Maria and Tabbone, Antoine and Fred, Ana (editors), 3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM), SciTePress, 2014.
Lee/Schramm/2013a Lee, Sangkyun and Schramm, Alexander. Preprocessing of Affymetrix Exon Expression Arrays. No. 3, Technische Universität Dortmund, 2013.
Lee/Wright/2013a Lee, Sangkyun and Wright, Stephen J.. Stochastic Subgradient Estimation Training for Support Vector Machines. In Latorre Carmona, Pedro and S\'anchez, J. Salvador and Fred, Ana L.N. (editors), Mathematical Methodologies in Pattern Recognition and Machine Learning, Vol. 30, pages 67--82, Springer, 2013.
Piatkowski/etal/2013a Piatkowski, Nico and Lee, Sangkyun and Morik, Katharina. Spatio-Temporal Random Fields: Compressible Representation and Distributed Estimation. In Blockeel, Hendrik and Kersting, Kristian and Nijssen, Siegfried and Zelezny, Filip (editors), Machine Learning Journal, Vol. 93, No. 1, pages 115--139, Springer, 2013.
Lee/2012a Lee, Sangkyun. Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation. In German Conference on Artificial Intelligence (KI 2012), pages 229--232, 2012.
Lee/etal/2012a Lee, Sangkyun and Stolpe, Marco and Morik, Katharina. Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. In Peter Flach and Tijl De Bie and Nello Cristianini (editors), Machine Learning and Knowledge Discovery in Databases, Vol. 7524, pages 387--402, Berlin, Heidelberg, Springer, 2012.
Lee/Wright/2012a Lee, Sangkyun and Wright, Stephen J.. ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. In International Conference on Pattern Recognition Applications and Methods (ICPRAM 2012), pages 223-228, 2012.
Lee/Wright/2012b Lee, Sangkyun and Wright, Stephen J.. Manifold Identification in Dual Averaging Methods for Regularized Stochastic Online Learning. In Journal of Machine Learning Research, Vol. 13, pages 1705--1744, 2012.
Piatkowski/etal/2012a Piatkowski, Nico and Lee, Sangkyun and Morik, Katharina. Spatio-Temporal Models For Sustainability. In Marwah, Manish and Ramakrishnan, Naren and Berges, Mario and Kolter, Zico (editors), Proceedings of the SustKDD Workshop within ACM KDD 2012, ACM, 2012.
Umaashankar/Lee/2012a Umaashankar, Venkatesh and Lee, Sangkyun. Optimization plugin for RapidMiner. No. 4, TU Dortmund University, 2012.
Lee/2011a Lee, Sangkyun. Optimization Methods for Regularized Convex Formulations in Machine Learning. University of Wisconsin--Madison, 2011.
Lee/Bockermann/2011a Lee, Sangkyun and Bockermann, Christian. Scalable stochastic gradient descent with improved confidence. In Big Learning -- Algorithms, Systems, and Tools for Learning at Scale, 2011.
Lee/etal/2011a Lee, Sangkyun and Schowe, Benjamin and Sivakumar, Viswanath and Morik, Katharina. Feature Selection for High-Dimensional Data with RapidMiner. No. 1, TU Dortmund University, 2011.
Lee/Wright/2011a Lee, Sangkyun and Wright, Stephen J.. Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning. In the 28th International Conference on Machine Learning, 2011.
Lee/Wright/2011b Lee, Sangkyun and Wright, Stephen J.. Manifold Identification in Dual Averaging Methods for Regularized Stochastic Online Learning. University of Wisconsin-Madison, 2011.
Lee/Wright/2009a Lee, Sangkyun and Wright, Stephen J.. Decomposition Algorithms for Training Large-scale Semiparametric Support Vector Machines. In Buntine, Wray and Grobelnik, Marko and Mladenic, Dunja and Shawe-Taylor, John (editors), Machine Learning and Knowledge Discovery in Databases, Vol. 5782, pages 1-14, Springer, 2009.
Lee/Wright/2009b Lee, Sangkyun and Wright, Stephen J.. Signal Processing Algorithms on Graphical Processing Units. In INFORMS Annual Meeting, 2009.
Lee/Wright/2009c Lee, Sangkyun and Wright, Stephen J.. Decomposition and Stochastic Subgradient Algorithms for Support Vector Machines. In 20th International Symposium on Mathematical Programming, 2009.
Lee/Wright/2008a Lee, Sangkyun and Wright, Stephen J.. Implementing Algorithms for Signal and Image Reconstruction on Graphical Processing Units. University of Wisconsin-Madison, 2008.
Lee/etal/2006a Lee, Sangkyun and Lee, S.-J. and Zhang, B.-T.. Combining Information-based Supervised and Unsupervised Feature Selection. In Isabelle Guyon, Steve Gunn, Masoud Nikravesh, Lofti A. Zadeh (editors), Feature Extraction: Foundations and Applications, Springer, 2006.
Lee/2005a Lee, Sangkyun. Integrating Different Species Pairwise Information Using Multiple Relational Embedding Techniques. Seoul National University, 2005.

Software

Supervised Master's Theses

Membership

Conference program committee / reviewer activities:

  • NIPS, ECML/PKDD, IEEE ICDM, IEEE ICDE, ECAI, DATA

Journal reviewer activities:

  • Optimization Methods and Software
  • IEEE Trans. Neural Networks and Learning Systems
  • Data Mining and Knowledge Discovery
  • Knowledge and Information Systems

Awards

  • Best student paper award, Journal Track (Machine Learning) of ECML/PKDD 2013
  • Samsung Scholarship, Samsung Foundation of Culture, 2005-2010