Professor Haesun Park
Haesun Park
Office: CODA Building
Phone: 404-385-2170
Fax: 404-385-7337
Email: hpark@cc.gatech.edu

Selected Publications

2022

  • S. Oh, H. Park, and X. Zhang,
    Hybrid clustering of single-cell gene expression and spatial information via integrated NMF and k-means,
    Frontiers in Genetics - Computational Genomics, to appear.
  • D. Chu, W. Shi, S. Eswar, and H. Park,
    An alternating rank-k nonnegative least squares framework (ARkNLS) for nonnegative matrix factorization,
    SIAM Journal on Matrix Analysis and Applications, to appear
  • S. Eswar, R. Kannan, R. Vuduc, and H. Park,
    ORCA: Outlier detection and Robust Clustering for Attributed graphs,
    Journal of Global Optimization, to appear

2021

2020

  • L. Manning, G. Ballard, R. Kannan, and H. Park,
    Parallel hierarchical clustering using rank-two nonnegative matrix factorization,
    27th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC20)}, Pune, India, December 18-19, 2020
  • S. Eswar, K. Hayashi, R. Kannan, G. Ballard, R. Vuduc, and H. Park,
    Distributed-memory parallel Symmetric Non-negative Matrix Factorization,
    Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC20), Atlanta, GA, November 15-20, 2020, IEEE Press, Article 74, pp. 1041-1054
  • K. Hayashi, S. Aksoy, C. Park, and H. Park,
    Hypergraph random walks, Laplacians, and clustering,
    Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM20), ACM, October 19-23, 2020, New York, NY, pp. 495-504 http://doi.org/10.1145/3340531.3412034
  • J. Whang, R. Du, S. Jung, G. Lee, B. Drake, Q. Liu, S. Kang, and H. Park,
    MEGA: Multi-view semi-supervised clustering of hypergraphs,
    The 46th International Conference on Very Large Data Bases (VLDB20)}, Tokyo, Japan, September 2020
  • A. Afshar, I. Perros, H. Park, C. Defilippi, Z. Yan, W. Stewart, J. Ho, and J. Sun,
    TASTE: Temporal and static tensor factorization for phenotyping electronic health records,
    The ACM Conference on Health, Inference, and Learning (CHIL20), Toronto, Canada, April 2020

2019

  • H. Kim, D. Choi, B. Drake, A. Endert, and H. Park,
    TopicSifter: Interactive search space reduction through targeted topic modeling,
    Proceedings of the IEEE Conference on Visual Analytics Science and Technology 2019
  • H. Kim, D. Katerenchuk, D. Billet, B. Li, and H. Park,
    Learning joint Gaussian representations for movies, actors, and literary characters,
    Proceedings of the AAAI Conference on Artificial Intelligence 2019

2018

  • R. Du, D. Kuang, B. Drake, and H. Park,
    Hierarchical Community Detection via Rank-2 Symmetric Nonnegative Matrix Factorization,
    Computational Social Networks
  • R. Kannan, G. Ballard, and H. Park,
    MPI-FAUN: An MPI-based framework for alternating-updating nonnegative matrix factorization,
    IEEE Transactions on Knowledge and Data Engineering, 30-3:544-558, 2018
  • I. Perros, E. Papalexakis, R. Vuduc, X. Yan, C. Defillippi, W. Sewart, J. Sun, and H. Park,
    SUSTain:Scalable unsupervised scoring for tensors and its application to phenotyping
    ACM SIG Conference on Knowledge Discovery and Data Mining (KDD18), London, UK, August 19-23, 2018
  • M. Kim, M. Choi, S. Lee, J. Tang, J. Choo, and H. Park
    PixelSNE: pixel-aligned stochastic neighbor embedding for efficient 2D visualization with just enough precision,
    EG/VGTC Conference on Visualization (EuroVis18), Brno, Czech Republic, June 4-8, 2018
  • M. Choi, S. Shin, J. Choi, S. Langevin, C. Bethune, P. Horne, N. Kronenfeld, R. Kannan, B. Drake, J. Choo, and H. Park,
    ExTopicTile: Tile-Based spatio-temporal visual analytics for anomalous event detection via ex- clusive topic modeling on social media,
    Proceedings of the ACM SIGCHI Conference (CHI18), Montreal, Canada, April 21-26, 2018
  • W. Lim, R. Du, and H. Park,
    CoDiNMF: Co-clustering of directed graphs via NMF,
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI18), 2018
  • J. Choo, H. Kim, E. Clarkson, Z. Liu, C. Lee, F. Li, H. Lee, R. Kannan, C. Stolper, J. Stasko, and H. Park,
    VisIRR: Visual Analytics for Information Retrieval and Recommendation for large-scale document data,
    ACM Transactions on Knowledge Discovery from Data, 8:1-8:20, 2018
  • B. Dong, M. Lin, and H. Park,
    Integer matrix approximation and data mining,
    Journal of Scientific Computing, 75-1: 198-224, 2018
  • R. Kannan, H. Woo, C. Aggarwal, and H. Park,
    Outlier detection for text data,
    Proceedings of the SIAM International Conference on Data Mining (SDM17).

2017

2016

  • H. Kim, J. Choo, A. Endert, and H. Park,
    InterAxis: steering scatterplot axes via observation-level interaction,
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 22(1):131-140, 2016.
  • G. Ballard, R. Kannan, and H. Park,
    A high-performance parallel algorithm for nonnegative matrix factorization,
    Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP16), pp. 9:1-9:11, 2016.
  • R. Kannan, M. Ishteva, B. Drake, and H. Park,
    Bounded matrix low rank approximation,
    Non-negative Matrix Factorisation Techniques: Advances in Theory and Applications, Ed. G.R. Naik, Springer Berlin Heidelberg, pp. 89-118, 2016.
  • Minsuk Choi, Jaeseong Yoo, Ashley S. Beavers, Scott Langevin, Chris Bethune, Sean McIntyre, Barry L. Drake, Jaegul Choo, and H. Park,
    Tile-Based Spatio-Temporal Visual Analytics via Topic Modeling on Social Media,
    Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST16), Baltimore, MD (Poster paper), 2016.

2015

  • D. Kuang, S. Yun, and H. Park,
    SymNMF: Nonnegative low-rank approximation of a similarity matrix for graph clustering
    Journal of Global Optimization , 62(3): 545-574, 2015.
  • N. Gillis, D. Kuang, and H. Park,
    Hierarchical clustering of hyperspectral images using rank-two nonnegative matrix factorization
    IEEE Transactions on Geoscience and Remote Sensing, 53(4): 2066-2078, 2015.
  • H. Kim, J. Choo, C. Reddy, and H. Park,
    Doubly supervised embedding based on label information and intrinsic clusters for visualization
    Neurocomputing, Vol. 150, Part B, pp. 570-582, 2015
  • J. Choo, C. Lee, C. Reddy, and H. Park,
    Weakly supervised nonnegative matrix factorization for user-driven clustering
    Data Mining and Knowledge Discovery, 29(6):1598-1621, 2015.
  • W. Lim, M. Kim, K. Jung, and H. Park,
    Double Nystrom method: an efficient and accurate Nystrom scheme for large-scale data sets
    Proceedings of the International Conference on Machine Learning (ICML15), Lille, France, July, 2015.
  • H. Kim, J. Choo, J. Kim, C. Reddy, and H. Park,
    Simultaneous discovery of common and discriminative topics via joint nonnegative matrix factorization
    Proceedings of ACM SIG Conference on Knowledge Discovery and Data Mining (KDD15), Sydney, Australia, August, 2015.
  • S. Kim, J. Lee, G. Lebanon, and H. Park,
    Estimating temporal dynamics of human emotions
    Proceedings of the Twenty-ninth AAAI Conference on Artificial Intelligence (AAAI15), Austin, TX, January, 2015.
  • S. Kim, J. Lee, G. Lebanon, and H. Park,
    Local context sparse coding
    Proceedings of the Twenty-ninth AAAI Conference on Artificial Intelligence (AAAI15), Austin, TX, January, 2015.
  • J. Fairbanks, R. Kannan, D. Bader, and H. Park,
    Behavioral clusters in dynamic graphs
    Parallel Computing, 47:38-50, 2015.
  • D. Kuang, J. Choo, and H. Park,
    Nonnegative matrix factorization for interactive topic modeling and document clustering
    Partitional Clustering Algorithms (M.E. Celebi, Ed.), pp. 215-243, 2015, Springer.

2014

  • J.Kim, Y. He, and H. Park,
    Algorithms for nonnegative matrix and tensor factorizations: A unified view based on block coordinate descent framework
    Journal of Global Optimization , 58(2): 285-319, 2014.
  • R. Kannan, M. Ishteva, and H. Park,
    Bounded matrix factorization for recommender system
    Knowledge and Information Systems, 39(3): 491-511, 2014.
  • J. Choo, B. Drake, and H. Park,
    Visual analytics for interactive exploration of large-scale document data via Nonnegative Matrix Factorization
    Proceedings for BigData Innovators Gathering (BIG) 2014, co-located with WWW2014, Seoul, Korea, 2014.
  • J. Choo, D. Lee, B. Dilkina, H. Zha, and H. Park,
    To Gather Together for a Better World:Understanding and leveraging communities in micro-lending recommendation
    Proceedings for the Twenty-third International Conference on World Wide Web (WWW), pp. 249-260, Seoul, Korea, , 2014.
  • J. Choo, C. Lee, D. Lee, H. Zha, and H. Park,
    Understanding and promoting micro-finance activities in Kiva.org
    Proceedings for the ACM Conference on Web Search and Data mining (WSDM14)}, pp. 583-592, NY, NY, 2014.
  • J. Choo. C. Lee, H. Kim, H. Lee, C. Reddy, B. Drake, and H. Park,
    PIVE:A Per-iteration visualization environment for supporting real-time interactions with computational methods,
    Proceedings for the IEEE Conference on Visual Analytics Science and Technology (VAST14), Winner of Best Poster Award, 2014.

2013

  • D. Kuang, and H. Park,
    Fast rank-2 nonnegative matrix factorization for hierarchical document clustering
    Proceedings of the ACM SIG Conference on Knowledge Discovery and Data Mining (KDD13), pp. 739-747 , 2013.
  • J. Choo, C. Lee, C. Reddy, and H. Park,
    UTOPIAN: User-driven Topic modeling based on interactive nonnegative matrix factorization
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 19-12, pp. 1992-2001, 2013.
  • M. Ishteva, L. Song, and H. Park,
    Unfolding Latent Tree Structures using 4th Order Tensors
    Proceedings of the International Conference on Machine Learning (ICML13), Atlanta, GA, 2013.
  • L. Song, M. Ishteva, A. Parikh, E. Xing, and H. Park,
    Hierarchical tensor decomposition of latent tree graphical models,
    Proceedings of the International Conference on Machine Learning (ICML13), Atlanta, GA, 2013.
  • J. Choo,
    Customizing computational methods for visual analytics with big data
    IEEE Computer Graphics and Applications, Special Issue: Big Data Visualization, 33-4, pp. 22-28, 2013.
  • C. Görg, Z. Liu, J. Kihm, J. Choo, J. Stasko, and H. Park,
    Combining Computational Analyses and Interactive Visualization for Document Exploration and Sensemaking in Jigsaw
    IEEE Transactions on Visualization and Computer Graphics (TVCG), , 19-10, pp. 1646-1663, 2013.
  • J. Choo, H. Lee, Z. Liu, J. Stasko, and H. Park,
    An interactive visual testbed system of dimension reduction and clustering for large-scale highdimensional data
    IS&T/SPIE Electronics Imaging 2013: Conference on Visualization and Data Analysis , Feb. 2013, Burlingame, CA, USA.
  • L. Song, B. Xie, and H. Park,
    Topic modeling via nonnegative matrix factorization on probability simplex,
    Proceedings for the Workshop on Topic Models: Computation, Application, and Evaluation (NIPS13), Neural Information Processing Systems Foundation Conference, Lake Tahoe, Nevada, December 10, 2013.
  • C. Lee, J. Choo, D. Chau, and H. Park,
    Interactive data analysis tool by augmenting MATLAB with semantic objects
    Proceedings for the thirteenth IEEE International Conference on Data Mining (ICDM13), ICDM-2013 Demo Workshop, 2013.
  • J. Kim, N.Ramakrishnan, M. Marwah, A. Shah, and H. Park,
    Regularization paths for sparse nonnegative least squares problems with applications to life cycle assessment tree discovery,
    Proceedings for the thirteenth IEEE International Conference on Data Mining (ICDM13), 2013.
  • C. Lee, J.Choo, D. Chau, and H. Park,
    Augmenting MATLAB with semantic objects for an interactive visual environment,
    IEEE International Conference on Data Mining Demo Paper, 2013.

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

  • E. Kwon, B. Choi, and H. Park,
    A personal computer-based parallel simulation system for on-line assessment of freeway operational strategies,
    the Proceedings for the 4th Annual ITS World Congress, 1998.

1997

  • L. Eldén and H. Park,
    Stability analysis and fast algorithms for triangularization of Toeplitz matrices
    Numerische Mathematik, 76-3, pp. 383-400, 1997.
  • J¨urgen G¨otze and H. Park,
    Schur-type methods based on subspace criteria,
    the Proceedings for the IEEE Int. Symp. on Circuits and Systems, pp. 2661-2664, Hong Kong, 1997.
  • E. Kwon, K. Yoo, and H. Park,
    Parallel simulation of freeway traffic flows on a personal computer-based distributed computing system,
    the Proceedings for the 3rd Annual ITS World Congress, pp. 36-42, 1997.

1996

1995

1994

  • L. Eldén and H. Park,
    Block downdating of least squares solutions
    SIAM Journal on Matrix Analysis and Applications, 15-3, pp. 1018-1034, 1994.
  • Å. Björck, L. Eldén, and H. Park,
    Accurate downdating of least squares solutions
    SIAM Journal on Matrix Analysis and Applications, 15-2, pp. 549-568, 1994.
  • H. Park
    ESPRIT direction-of-arrival estimation in the presence of spatially correlated noise,
    SIAM Journal on Matrix Analysis and Applications, 15-1, pp. 185-193, 1994.
  • A. Anda and H. Park,
    Fast plane rotations with dynamic scaling,
    SIAM Journal on Matrix Analysis and Applications, 15-1, pp. 162-174, 1994.
  • D.-Z. Du and H. Park,
    On competitive algorithms for group testing,
    SIAM Journal on Computing, 23-5, pp. 1019-1025, 1994.
  • L. Eldén and H. Park,
    Perturbation analysis for block downdating of a Cholesky decomposition,
    Numerische Mathematik, 68, pp. 457-467, 1994.
  • S. Van Huffel and H. Park,
    Parallel tri- and bi-diagonalization of bordered bidiagonal matrices,
    Parallel Computing, 20, pp. 1107-1128, 1994.
  • L. Eld´en, S. Van Huffel, and H. Park,
    Fast algorithms for exponential data modeling,
    the proceedings for IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol 4, pp. 25-28, Adelaide, Australia, April 19-22, 1994.

1993

  • L.M. Ewerbring and H. Park,
    An algorithm for the generalized singular value decomposition on massively parallel computers,
    Journal of Parallel and Distributed Computing, 17, pp. 267-276, 1993.
  • V. Hari and H. Park,
    A real algorithm for the Hermitian eigenvalue decomposition,
    BIT, 33, pp. 158-171, 1993.
  • L. Eld´en and H. Park,
    Fast and accurate Toeplitz matrix triangularization for linear prediction,
    IEEE workshop on VLSI Signal Processing VI, pp. 343-352, 1993.
  • S. Van Huffel and H. Park,
    Improved parallel algorithm for band matrix reconstruction,
    Proceedings of the ProRISC IEEE Workshop on Circuits, Systems and Signal Processing, pp. 275-280, Houthalen, Belgium, March 24-25, 1993.

1992

  • H. Park
    On multiple error detection in matrix triangularizations using checksum methods,
    Journal of Parallel and Distributed Computing, 14, pp. 90-97, 1992.
  • A.A. Anda and H. Park,
    Fast computation of eigenvalue decompositions on vector architectures,
    Advances in Optimization and Parallel Computing, pp. 26-41, North-Holland, 1992.

1991

  • H. Park
    A parallel algorithm for the unbalanced orthogonal Procrustes problem,
    Parallel Computing, 17, pp. 913-923, 1991.
  • L.M. Ewerbring and H. Park,
    An algorithm for the generalized singular value decomposition on massively parallel computers,
    Proceedings for the ACM International Conference on Supercomputing, pp. 136-145, 1991.

1990

  • P.J. Eberlein and H. Park,
    Efficient implementation of Jacobi algorithms and Jacobi sets on distributed memory architectures,
    Journal of Parallel and Distributed Computing, special issue on
    Algorithms for Hypercube Computers, 8, pp. 358-366, 1990.
  • H. Park
    Efficient diagonalization of oversized matrices on a distributed-memory multiprocessor,
    Annals of Operations Research, 22, pp. 253-269, 1990.
  • H. Park
    Matrix diagonalization algorithms for oversized problems on a distributed-memory multiprocessor,
    Mathematics in Signal Processing II, ed. J.G. McWhirter, Oxford University Press, pp. 615-630, 1990.
  • D. Boley, R. Maier, P.J. Eberlein, and H. Park,
    The parallel solution of the matrix eigenproblem with applications in control theory,
    Signal Processing, Scattering and Operator Theory, and Numerical Methods,
    ed. M.A. Kaashoek, J.H. Van Schuppen, and A.C.M. Ran, Birkhauser, pp. 373-380, 1990.
  • L.M. Ewerbring and H. Park,
    Computing the generalized singular value decomposition on the Connection Machine,
    Proceedings for SPIE conference on Advanced Signal Processing Algorithms, Architectures, and Implementations, pp. 392-405, 1990.

1989

  • F.T. Luk and H. Park,
    A proof of convergence for two parallel Jacobi SVD algorithms,
    IEEE Transactions on Computers, 38(6), pp. 806-811, 1989.
  • F.T. Luk and H. Park,
    On parallel Jacobi orderings,
    SIAM Journal on Scientific and Statistical Computing, 10(1), pp. 18-26, 1989.
  • P.J. Eberlein and H. Park,
    Eigensystem computation on hypercube architectures,
    the Proceedings of the Fourth Conference on Hypercube Concurrent Computers and Application, pp. 689-692, 1989.

1988

  • F.T. Luk and H. Park,
    An analysis of algorithm-based fault tolerance techniques,
    Journal of Parallel and Distributed Computing, pp. 172-184, 1988.
  • F.T. Luk and H. Park,
    Fault-tolerant matrix triangularizations on systolic arrays,
    IEEE Transactions on Computers, 37(11), pp. 1434-1438, 1988.
  • H. Park
    Multiple error algorithm-based fault tolerance for matrix triangularizations,
    Proceedings for SPIE Conference on Advanced Algorithms and Architectures for Signal Processing III, Vol. 975, pp. 258-267, 1988.
  • F.T. Luk and H. Park,
    Equivalence and convergence of parallel Jacobi SVD methods,
    Proceedings for SPIE Conference on Advanced Algorithms and Architectures for Signal Processing, pp. 152-159, 1987.