Professor Yuh-Jye Lee

Contact

• Email: yuhjye@math.nctu.edu.tw
• Tel: +886-3-571-2121 ext.56420
• Fax: +886-3-572-4679
• Address: Department of Applied Mathematics, National Chiao Tung University,1001 Ta Hsueh Road, Hsinchu, Taiwan 30050, ROC

Teaching

• Fall Semester, 2023：
  • Topical Mathematical Modeling and Computing (I)
  • Machine Learning
• Spring Semester, 2023：
  • Compressed sensing
  • Colloquium

Vitae

• Education
  • 1995–2001 Ph.D. in Computer Sciences, University of Wisconsin at Madison, USA
  • 1990–1992 M.Sc. in Applied Mathematics, National Tsing Hua University, Taiwan
  • 1986–1990 B.Sc. in Applied Mathematics, Chinese Culture University, Taiwan
• Research Areas
  • Big Data & Data Science
  • Data Mining
  • Machine Learning
  • Numerical Optimization
  • Operations Research
  • Information Security
• Positions, Honors and Awards
  【Honours and Awards】
   
  2010 2005-2010 Top Cited Paper Award ELSEVIER
  2010 Excellent Research Award NTUST
  2009 Excellent Research Award NTUST
  2008 Outstanding Teaching Award NTUST
  2007 Excellent Teaching Award NTUST
  2006 Excellent Teaching Award NTUST
  
  【Work  Experience】
  
  Associate Professor Dept. of Computer  Science  and Information Engineering National  Taiwan University of Science  and Technology,  Taiwan August 2007–January  2013
  Assistant Professor Dept. of Computer  Science  and Information Engineering, National  Taiwan University of Science  and Technology,  Taiwan August 2002–July 2007
  Assistant Professor Dept. of Computer  Science  and Information Engineering, National  Chung Cheng University, Taiwan August 2001–July 2002 Ajunct Assistant Professor Dept. of Applied Mathematics, Providence University, Taiwan August 2005– July 2006
  Research Assistant Dept. of Computer  Sciences, University of Wisconsin  at Madison, USA, 1998–2001
  Teaching Assistant Dept. of Computer  Sciences University of Wisconsin  at Madison, USA, 1996–2001
• Recent Research Projects
  From  Ministry of Science and Technology (MOST/NSC)
  2014–2016 Solve Extremely  Large Classification Problem  via Online Learning Algorithms  and MapReduce Framework
  2013–2015 Making Fusion Between the Range of Anomaly Detection  Algorithms  in Order to Obtain Solution that  Equivalent  to Single and Strong Algorithm
  2013–2014 Continuous User Identification via Text Classification and Data MiningI
  2010–2013 Cloud Service  Defense-in-depth  Security  Technology Research  and Development (Main)
  2010–2013 Anomaly Detection  Based on Could Clients Behavior  Profiling  (Component 1)
  2009–2010 Anomaly Detection  via Online Over-Sampling Principal  Component  Analysis
  
  
  From  Intel-NTU Connected Context Computing Center :
  Funded by Intel corporation, NSC and National  Taiwan University
  2012–2015 Distributed Anomaly Detection  Systems  for M2M PI Applications
   
  From  Institute for Information Indutry:
  2013 Time Series Missing Data Imputation and Data Fusion
  2012 Abnormal  Behavior  of the Virtual System Modeling Co-
   
  From  Trend Micro:
  2011 A Machine  Learning Approach  for Malicious  URLs PI Detection
   
  From  Chunghwa Telecom  Laboratories:
  2010 Distributed and Hierarchical Intrusion Detection Co-
  2009 and Event Analysis System Intrusion Detection  and Event Analysis System 
   
  From  Chalet Tech (Supported by SBIR):
  2009 Expert System  for Database  Performance and PI Security  Protection System

Selected Publications

(A)   Refereed Papers：

1. Hsing-Kuo Pao, Yuh-Jye Lee, and  Chun-Ying Huang.  “Statistical Learning  Methods  for  Information Security: Fundamentals and Case Studies”,  Applied Stochastic Models in Business  and Industry,  Vol. 31, No. 2, Pages 97-113, 2015.  (SCI)
2. Jain-Shing Wu, Chih-Ta Lin, Yuh-Jye Lee, and  Song-Kong Chong.  “Keystroke and  Mouse  Movement Profiling  for Data Loss Prevention”, Journal of Information Science  and  Engineering,  Vol. 31, No.  1, Pages 23-42, 2015. (SCI)
3. Yi-Ren Yeh, Su-Yun Haung, Hsing-Kuo Pao, and Yuh-Jye Lee.  “A Review  of Reduced  Kernel Trick in Machine  Learning”, Journal of the Chinese Statistical Association,  Vol. 52, No. 1, Pages 85-114, 2014.
4. Yuh-Jye Lee, Yi-Ren Yeh, and Yu-Chiang Frank Wang. “Anomaly  Detection  via Online Over-Sampling Principal  Component  Analysis”,  IEEE Transactions on Knowledge and Data Engineering, Vol. 25, No. 7, Pages 1460-1470, 2013. (SCI)
5. Chien-Chung Chang, Hsing-Kuo Pao, and  Yuh-Jye Lee.  “An RSVM based  Two-teachers-one-student Semi-supervised Learning Algorithm”, Neural  Networks, Vol. 25, Pages 57-69, 2012. (SCI)
6. Chih-Cheng Chang, Li-Jen Chien and Yuh-Jye Lee. “A Novel Framework for Multi-class  Classification via Ternary  Smooth  Support  Vector  Machine”, Pattern  Recognition,  Vol. 44, Issue  6, Pages 1235-1244, 2011. (SCI)
7. Pei-Chun Chen, Kuang-Yao Lee, Tsung-Ju Lee, Yuh-Jye Lee and  Su-Yun Huang.  “Multiclass Support Vector Classification via Coding and Regression”,  Neurocomputing, Vol. 73, Issue  7-9, Pages 1501-1512, 2010. (SCI)
8. Li-Jen Chien, Chien-Chung Chang and  Yuh-Jye Lee.  “Variant  Methods  of Reduced  Set Selection  for Reduced  Support  Vector  Machines”,  Journal of Information Science  and Engineering, Vol. 26, No. 1, Pages 183-196, 2010. (SCI)
9. Chun-Nan Hsu, Han-Shen Huang, Yu-Ming Chang and Yuh-Jye Lee. “Periodic  Step-size Adaptation  in Second-order Gradient Descent  for Single-pass  On-line Structured Learning”, Machine  Learning, Vol. 77, Issue  2-3, Special  Issue  for Structured Prediction,  Pages 195-224, 2009 (SCI)
10. Wolfgang  Härdle,  Yuh-Jye Lee,  Dorothea  Schäfer  and  Yi-Ren Yeh.   “Variable   Selection   and  Over- sampling in the  use  of Smooth  Support  Vector  Machines  for  Predicting  the  Default  Risk of Com- panies”,  Journal of Forecasting, Vol. 28 Issue  6, Pages 512-534, 2009. (SSCI)
11. Yi-Ren Yeh, Su-Yun Huang, Yuh-Jye Lee. “Nonlinear Dimension  Reduction  with  Kernel Sliced Inverse Regression”,  IEEE Transactions on Knowledge and Data Engineering, Vol. 21, No. 11,  Pages 1590-1603, 2009. (SCI)
12. Yuh-Jye Lee,  Chien-Chung Chang and  Chia-Huang Chao.  “Incremental Forward  Feature  Selection with  Application  to Microarray Gene Expression  Data”, Journal of Biopharmaceutical Statistics, Vol. 18, Issue  5, Pages 827-840, 2008. (SCI)
13. Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin and  Su-Yun Huang.  “Model Selection  for Support Vector  Machines  via  Uniform  Design”, Computational Statistics and  Data Analysis, Vol.  52, Issue  1, Pages 335-346, 2007. (SCI)
14. Yuh-Jye Lee and  Su-Yun Huang.   “Reduced  Support  Vector  Machines:   A  Statistical Theory”,  IEEE Transactions on Neural  Networks, Vol. 18, No. 1, Pages 1-13, 2007. (SCI)
15. Yuh-Jye  Lee,  Wen-Feng Hsieh and  Chien-Ming Huang.  “ϵ–SSVR:  A smooth support vector machine for ϵ–insensitive regression”, IEEE Transactions on Knowledge and Data Engineering,  Vol. 17, No. 5, Pages 678-685, 2005. (SCI)
16. Yuh-Jye Lee, Olvi L. Mangasarian and W. H. Wolberg.  “Survival-Time  Classification of Breast  Cancer Patients”,  Computational Optimization and Applications,  25, Pages 151-166, 2003. (SCI)
17. Yuh-Jye  Lee and Olvi L. Mangasarian. “SSVM:  A Smooth  Support  Vector  Machine  for Classification”, Computational Optimization and Applications,  20, Pages 5-22, 2001. (SCI)
18. Chih Chang and Yuh-Jye Lee. “ A Non-weakly Balanced Game with Nonempty Bargaining Set”, Journal of Mathematical Economics  22, Pages 195-198, 1993.
 

(B)   Conference Papers：

1. Wei-Chih Lai, Po-Han Huang, Yuh-Jye Lee, and Alvin Chiang, “A distributed ensemble scheme for non- linear  support vector machine”, Tenth IEEE International Conference on Intelligent Sensors,  Sensor Networks and Information Processing, ISSNIP 2015, April 7-9, 2015.
2. Xing-Yu Chen, Hsing-Kuo Pao, and Yuh-Jye Lee, “Efficient  traffic speed  forecasting based  on massive heterogenous historical data”,  2014  IEEE International Conference on Big Data, October 27-30, 2014.
3. Yang-Chi Shen, Alvin Chiang, Yi-Ren Yeh, and Yuh-Jye Lee, “Continuous monitoring and distributed anomaly detection for ambient factors”, 2014 IEEE  International Conference on Internet of Things, September 1-3, 2014.
4. Link Jaw, and Yuh-Jye Lee, “Engine Diagnostics  in the Eyes of Machine  Learning”, ASME Turbo Expo. 2014: Turbin Technical Conference and Exposition, June 16-20, 2014.
5. Shan-Hung Wu, Man-Ju Chou, Chun-Hsiung Tseng, Yuh-Jye Lee, and Kuan-Ta Chen, “Detecting  in-situ identity fraud  on social  network services: a case  study  on facebook”, ACM 23rd International World Wide Web Conference,  WWW ’14, April 7-11, 2014.
6. Min-Sheng Lin, Chien-Yi Chiu, Yuh-Jye Lee, and Hsing-Kuo Pao, “Malicious  URL filtering - A big data application”, 2013  IEEE International Conference on Big Data, October 6-9, 2013.
7. Lin Xu, Yi-Ren Yeh, Yuh-Jye Lee, and  Jing Li,  “A hierarchical framework using  approximated local outlier factor  for efficient anomaly detection”, The 3rd International workshop on Sensor  Networks for Intelligence Gathering  and Monitoring,  ANT/SEIT, June 25-28, 2013.
8. Ming-Hen Tsai, Yi-Ren Yeh, Yuh-Jye Lee, and  Yu-Chiang F. Wang, “Solving  nonlinear SVM in linear time?  A Nystrom approximated SVM with  applications to image  classification,” The 13th IAPR Con- ference on Machine  Vision Applications (MVA), May 2013, (nominated for MVA 2013 paper  awards).
9. Hsing-Kuo Pao, Yan-Lin Chou and  Yuh-Jye Lee. “Malicious  URL detection based  on Kolmogorov  com- plexity  estimation”, The 2012 IEEE/WIC/ACM International Conference on Web Intelligence, Macau, December  4-7, 2012.
10. Ding-Jie Huang, Kai-Ting Yang, Chien-Chun Ni, Wei-Chung Teng, Tien-Ruey Hsiang and Yuh-Jye Lee, “Clock skew  based  client  device  identification in cloud  environments”, The 26th  IEEE International Conference on Advanced Information Networking and Applications (IEEE AINA-2012), Fukuoka, Japan, March 26-29, 2012.
11. Yi-Cheng Tseng and Yuh-Jye Lee. “Rank-r updating techniques for fast exact  cross-validation”, Indus- trial  Conference on Data Mining, New York, USA, 2011.
12. Yu-Wei  Chao, Yi-Ren Yeh, Yu-Wen Chen, Yuh-Jye Lee, and Yu-Chiang Frank Wang, “Locality-constrained group  sparse representation for  robust face  recognition,” IEEE  International Conference on Image Processing, Brussels,  Belgium, 2011.
13. Li-Jen  Chien, Zhi-Peng Kao and Yuh-Jye Lee.  “Smooth  LASSO for classification”, The 2010 Conference on Technologies and Applications of Artificial Intelligence, Hsinchu, Taiwan, 2010.
14. Chien-Chung Chang,  Yuh-Jye Lee and  Hsing-Kuo Pao.   “A Passive-Aggressive algorithm  for  semi- supervised learning”, The 2010 Conference on Technologies and Applications of Artificial Intelligence, Hsinchu, Taiwan, 2010.
15. Chien-Yi Chiu, Yuh-Jye Lee,  Chien-Chung Chang,  Wen-Yang Luo and  Hsiu-Chuan Huang.   “Semi- supervised learning for  false  alarm  reduction”, Industrial Conference on Data Mining, Berlin, Ger- many, 2010.
16. Li-Jen Chien, Yuh-Jye Lee, Zhi-Peng Kao, and Chih-Cheng Chang. “Robust 1-Norm soft margin  smooth support vector machine”, International Conference on Intelligent Data Engineering  and Automated Learning, Paisley, UK, 2010.
17. Chun-Nan Hsu, Yu-Ming Chang, Han-Shen Huang and Yuh-Jye Lee. “Periodic  step-size  adaptation for single-pass on-line learning”, Neural  Information Processing Systems,  Vancouver, B.C., Canada, 2009.
18. Yi-Ren Yeh, Zheng-Yi Lee and Yuh-Jye Lee. “Anomaly detection via over-sampling principal component analysis”, KES International Symposium on Intelligent Decision Technologies,  Himeji, Japan, 2009.
19. Heng-Sheng Lin, Hsing-Kuo Pao, Ching-Hao Mao, Hahn-Ming Lee, Tsuhan  Chen and  Yuh-Jye Lee. “Adaptive  alarm  filtering by  causal correlation consideration in intrusion detection”, KES  Interna- tional  Symposium on Intelligent Decision Technologies,  Himeji, Japan, 2009.
20. Tsong Song Hwang,  Tsung-Ju Lee and  Yuh-Jye Lee.   “A three-tier IDS via  data  mining  approach”, ACM Workshop  on  Mining Network Data, in conjunction with  Joint  International Conference on Measurement and Modeling of Computer  Systems,  San Diego, California, USA, 2006.
21. Yuh-Jye  Lee and Yi-Ren Yeh. “Ranking the rules  and instances of decision trees”,  Industrial Conference on Data Mining, Leipzig, Germany, 2006.
22. Kun-lin Chiang, Lih-Ren Jen and  Yuh-Jye Lee.  “A data  mining  application for  personal loan”,  TAAI Conference,  Kaohsiung, Taiwan, 2005.
23. Hsing-Kuo Pao, Shou-Chih Chang and Yuh-Jye Lee. “Model trees  for hybrid  data  type  classification”, International Conference on Intelligent Data Engineering  and Automated Learning, Queensland,  Aus- tralia,  2005.
24. Chien-Chung Chang and Yuh-Jye Lee.  “Generating  the reduced set  by systematic sampling ”, Inter- national Conference on Intelligent Data Engineering  and Automated Learning, Exeter, UK, 2004.
25. Li-Jen Chien and  Yuh-Jye Lee.  “Clustering model  selection for reduced support vector machines ”, International Conference on Intelligent Data Engineering  and Automated Learning, Exeter, UK, 2004.
26. Yuh-Jye Lee, Hung-Yi Lo and Su-Yun Huang.  “Incremental reduced support vector machines”, Inter- national Conference on Informatics, Cybernetics and Systems,  Kaohsiung, Taiwan, 2003.
27. Yuh-Jye Lee and Chia-Huang Chao. “A data  mining  application to leukemia microarray gene  expres- sion  data  analysis”, International Conference on Informatics, Cybernetics and  Systems,  Kaohsiung, Taiwan, 2003.
28. Yuh-Jye Lee and  Olvi L.  Mangasarian.  “RSVM: Reduced  Support  Vector  Machines”,  The First SIAM International Conference on Data Mining, Chicago, 2001.
29. Yuh-Jye Lee and Olvi L. Mangasarian. “SSVM:  A Smooth  Support  Vector  Machine”,  Philadelphia IN- FORMS, November 7-10, 1999.

(C)   Others：

1. 1. Yuh-Jye Lee, Yi-Ren Yeh and Hsing-Kuo Pao, “Introduction to Support Vector Machines and Their Applications in Bankruptcy Prognosis,” Handbook of Computational Finance. (http://www.rmi.nus. edu.sg/csf/webpages/)
2. 2. Yuan-chin Ivan Chang, Yuh-Jye Lee, Hsing-Kuo Pao, Mei-Hsien Lee and Su-Yun Huang in Chun-houh Chen, Wolfgang Härdle and Antony Unwin (editors). “Data Visualization via Kernel Machines”, Hand- book of Computational Statistics (Volume III), Data Visualization, 2006.
3. 3. Yuh-Jye Lee, Olvi L. Mangasarian and W. H. Wolberg. “Breast Cancer Survival and Chemotherapy: A Support Vector Machine Analysis”, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Vol. 55, 2000.

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