Welcome to Cho-Jui Hsieh's Home Page

My name is Cho-Jui Hsieh. I am a Ph.D. student in University of Texas at Austin supervised by Prof. Inderjit Dhillon. I also work closely with Prof. Pradeep Ravikumar. Before coming here, I received my master degree in National Taiwan University with a supervision of Prof. Chih-Jen Lin. My research mainly focus on machine learning and optimization. Please see my Curriculum Vitae for further information.

E-Mail: cjhsieh_AT_cs.utexas.edu

Education

Ph.D student, Department of Computer Science, University of Texas at Austin, 2010 - now.

National Taiwan University, Taipei, Taiwan

M.S., Department of Computer Science and Information Engineering, 2007 - 2009
B.S., Department of Computer Science and Information Engineering, 2003 - 2007
B.S., Department of Mathematics, 2004-2007

Work Experience

IBM TJ Watson Research Center

Summer Intern, Jun 2013 - Aug 2013.

LinkedIn

Intern in SNA (Social Network Analysis) team, May 2012 - Aug 2012.
Developed models for organizational overlap on socianl network and its applications.
Work published in WWW 2013.

Google Inc, Taipei, Taiwan

Collaborate with Beijing research team, May 2008 - Sep 2008.
Studied parallel algorithms for training the kernel SVM and logistic regression.
Using explicit feature mapping to improved the training and prediction speed of the polynomial kernel SVM. Applied this technique to build an efficient dependency parser for machine translation.
Work published in JMLR.

Institute of Plant and Microbial Biology, Academia Sinica, Taiwan

Research assistent, Mar 2008 - May 2008.

Publications

C.-J. Hsieh, M. Tiwari, D. Agarwal, L. Huang, S. Shah Organizational Overlap on Social Networks and its Applications. ACM WWW International conference on World Wide Web (WWW), 2013.
H.-F. Yu, C.-J. Hsieh, S. Si, I. S. Dhillon, Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. IEEE International Conference on Data Mining(ICDM), December 2012 , best paper award.
C.-J. Hsieh, I. S. Dhillon, P. Ravikumar, A. Banerjee, A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. Advances in Neural Information Processing Systems (NIPS) 25, 2012
C.-J. Hsieh, K.-Y. Chiang, I. S. Dhillon, Low-Rank Modeling of Signed Networks. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012
C.-J. Hsieh, M. A. Sustik, I. S. Dhillon, P. Ravikumar, Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. Advances in Neural Information Processing Systems (NIPS) 24, 2011 Code
C.-J. Hsieh, I. S. Dhillon, Fast Coordinate Descent Methods with Variable Selection for Non-negative Matrix Factorization. The 17th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2011) Code
H.-F. Yu, C.-J. Hsieh, K.-W. Chang, and C.-J. Lin, Large linear classification when data cannot fit in memory. KDD 2010 best research paper award. code. A short version appears in IJCAI 2011. A journal version appears in ACM Transactions on Knowledge Discovery from Data (TKDD), Volumn 5 Issue 4 (2012).
G.-X. Yuan, K.-W. Chang, C.-J. Hsieh, and C.-J. Lin. A Comparison of Optimization methods and software for large-scale L1-regularized linear classification . Journal of Machine Learning Research 11(2010), 3183-3234
Y.-W. Chang, C.-J. Hsieh, K.-W. Chang, M. Ringgaard, and C.-J. Lin. Training and Testing Low-degree Polynomial Data Mappings via Linear SVM . Journal of Machine Learning Research 11(2010), 1471--1490
H.-Y. Lo, K.-W. Chang, S.-T. Chen, T.-H. Chiang, C.-S. Ferng, C.-J. Hsieh, Y.-K. Ko, T.-T. Kuo, H.-C. Lai, K.-Y. Lin, C.-H. Wang, H.-F. Yu, C.-J. Lin, H.-T. Lin and S.-d. Lin. An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes. JMLR Workshop and Conference Proceedings V.7, 57-64, 2009 (Third Place of the KDDCup'09 Slow Track).
F.-L. Huang, C.-J. Hsieh , K.-W. Chang, and C.-J. Lin. Iterative scaling and coordinate descent methods for maximum entropy models. Journal of Machine Learning Research 11(2010), 581-614. A short version appears as a short paper in ACL-IJCNLP 2009.
R.-E. Fan, K.-W. Chang, C.-J. Hsieh, and C.-J. Lin. LIBLINEAR: A library for large linear classification . Journal of Machine Learning Research 9(2008), 1871-1874. Note that we include some implementation details in the appendices of this paper.
S. S. Keerthi, S. Sundararajan, K.-W. Chang, C.-J. Hsieh, and C.-J Lin. A sequential dual method for large scale multi-class linear SVMs . KDD 2008.
C.-J. Hsieh, K.-W. Chang, C.-J. Lin, S. S. Keerthi, and S. Sundararajan. A dual coordinate descent method for large-scale linear SVM. ICML 2008
K.-W. Chang, C.-J. Hsieh, C.-J. Lin. Coordinate descent method for large-scale L2-loss linear SVM . Journal of Machine Learning Research 9(2008), 1369-1398

Softwares

LIBPMF:
A parallel matrix factorization library. It's very fast for large-scale data.
NMF_CD:
Fast coordinate descent methods for non-negative matrix factorization.
QUIC:
The QUadratic Inverse Covariance algorithm implements the l1 regularized Gaussian maximum likelihood estimation.
LIBLINEAR:
A linear support vector machine (SVM) library. It's very fast for large-scale data.
Hotter or Notter:
A large-scale photo ranking system. Photos come from Hot or Not.

Selected Awards

IBM PhD Fellowship 2013-2014.
Best Paper Award, ICDM 2012.
Best Research Paper Award, KDD 2010.
Best Master's Thesis Award, Institute of Information and Computing Machinery, 2009.
Third Prize in the slow track of KDDCUP 2009, An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes
Winner in SVM track of PASCAL Large Scale Learning Challenge in ICML 2008 workshop
Honorary member of the Phi Tau Phi Scholastic Honor Society (top 3% among 156 graduating master students)
Presidential award, National Taiwan University, 2 times (top 5% undergraduate student)
International Olympiad in Informatics, Taiwan Representation (top 4 of Taiwan)
Second Prize of National College Programming Contest, Taiwan (with Kai-Wei Chang and Peng-Ren Cheng)
Six Place in ACM ICPC Asia Regional programming, 2003 and 2006 (with Kai-Wei Chang and Peng-Ren Cheng)
Second Place in National High School Programming Contest, 2003