Zhuang (John) Wang


Email: <MyLegalFirstName>@temple.edu

 

Short Bio

I work at Skytree, a machine learning startup. I was a Managing Consultant of IBM Global Business Services, where I was focused on bridging science and business by consulting innovative Big Data & Analytics solutions for business innovations in a variety of industries. Prior to that, I was a Research Scientist with Siemens Research, where I was responsible for machine learning and data mining R&D. I earned my Ph.D. in Computer Science (machine learning and data mining) at Temple Univ., Philadelphia, in 2010 and my B.A. in Electronic Commerce at Wuhan Univ. China, in 2006.

Research Interests

Large-scale data classification

Support Vector Machine

Online learning

Multiple Instance Learning

Machine learning (in general)

 

Selected Publications

1.        Large-scale Non-linear Classification: Algorithms and Evaluations (Tutorial)

Wang, Z.

AAAI Conf. on Artificial Intelligence (AAAI), 2014, to appear.

Int. Joint Conf. on Artificial Intelligence (IJCAI), 2013. [tutorial homepage]

 

2.        BudgetedSVM: A Toolbox for Scalable SVM Approximations [pdf] [open source software]

Djuric, N., Lan. L., Vucetic, S. and Wang, Z.

Journal of Machine Learning Research (JMLR), 2013.

This toolbox is designed for approximately training non-linear SVM on large-scale, high-dimensional data when it CANNOT fit into memory. It can be treated as a missing link between LibLinear and LibSVM, combining efficiency of linear SVM with accuracy of kernel SVM models.

 

3.        Log-based Predictive Maintenance

Wang, Z., Fradkin, D. and Moerchen, F.

US Patent pending, 2012.

 

4.        Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training [pdf] [codes]

Wang, Z., Crammer, K and Vucetic, S.

Journal of Machine Learning Research (JMLR), 2012.

 

5.        Scaling up Kernel SVM on Limited Resources: a Low-rank Linearization Approach [pdf] [codes]

Zhang, K., Lan, L., Wang, Z., and Moerchen, F.

Int. Conf. on Artificial Intelligence and Statistics (AISTATS), 2012.

 

6.        Mixture Model for Multiple Instance Regression and Applications in Remote Sensing [pdf] [data]

Wang, Z., Lan, L. and Vucetic, S.

IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2012.

 

7.        Trading Representability for Scalability: Adaptive Multi-Hyperplane Machine for Nonlinear Classification [pdf] [codes]

Wang, Z., Djuric, N., Crammer, K. and Vucetic, S.

 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD), 2011, (Oral presentation AR: 56/714 = 7.8%)

 

8.        An Active Learning Algorithm Based on Parzen Window Classification [pdf]

 Lan, L., Shi, H., Wang, Z. and Vucetic, S., 

Journal of Machine Learning Research (JMLR): W&C Proc. 2010 AISTATS Active Learning Challenge, (our results ranked as the 5th in the competition)

 

9.        Multi-Class Pegasos on a Budget [pdf]

Wang, Z., Crammer, K and Vucetic, S.  

Int. Conf. on Machine Learning (ICML), 2010

 

10.    Online Training on a Budget of Support Vector Machines using Twin Prototypes [pdf] 

Wang, Z. and Vucetic, S.

Statistical Analysis and Data Mining Journal (SAM), 2010.

 

11.    Online Passive-Aggressive Algorithms on a Budget [pdf]   

Wang, Z. and Vucetic, S.

Int. Conf. on Artificial Intelligence and Statistics (AISTATS), 2010.

 

12.    Fast Online Training of Ramp Loss Support Vector Machines [pdf] 

Wang, Z. and Vucetic, S.,

IEEE Int. Conf. on Data Mining (ICDM), 2009, (Oral presentation AR: 70/786 = 8.9%)

 

13.    Compressed Kernel Perceptrons [pdf] 

Vucetic,S., Coric, V. and Wang, Z.,

IEEE Data Compression Conf. (DCC), 2009, (Oral presentation)

 

14.    Twin Vector Machines for Online Learning on a Budget [pdf]

Wang, Z. and Vucetic, S. 

SIAM Conf. on Data Mining (SDM), 2009, (Oral presentation AR: 55/351 = 15.67%)

 

15.    Aerosol Optical Depth Prediction from Satellite Observations by Multiple Instance Regression [pdf]

Wang, Z., Radosavljevic, V., Han, B., Obradovic, Z. and Vucetic, S.

SIAM Conf. on Data Mining (SDM), 2008, (Oral presentation AR: 40/282 = 14.18%)

 

 

         

 

Last Update: Apr., 2014