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Publications of Author

1. Ivor W. Tsang, James T. Kwok
   Efficient Hyperkernel Learning Using Second-Order Cone Programming. [Citation Graph (0, 0)][DBLP]
   ECML, 2004, pp:453-464 [Conf]
   
2. Ivor W. Tsang, András Kocsor, James T. Kwok
   Diversified SVM Ensembles for Large Data Sets. [Citation Graph (0, 0)][DBLP]
   ECML, 2006, pp:792-800 [Conf]
   
3. James T. Kwok, Ivor W. Tsang
   Learning with Idealized Kernels. [Citation Graph (0, 0)][DBLP]
   ICML, 2003, pp:400-407 [Conf]
   
4. James T. Kwok, Ivor W. Tsang
   The Pre-Image Problem in Kernel Methods. [Citation Graph (0, 0)][DBLP]
   ICML, 2003, pp:408-415 [Conf]
   
5. Ivor W. Tsang, James T. Kwok, Kimo T. Lai
   Core Vector Regression for very large regression problems. [Citation Graph (0, 0)][DBLP]
   ICML, 2005, pp:912-919 [Conf]
   
6. Ivor W. Tsang, James T. Kwok
   Ensembles of Partially Trained SVMs with Multiplicative Updates. [Citation Graph (0, 0)][DBLP]
   IJCAI, 2007, pp:1089-1094 [Conf]
   
7. Ivor W. Tsang, András Kocsor, James T. Kwok
   Efficient kernel feature extraction for massive data sets. [Citation Graph (0, 0)][DBLP]
   KDD, 2006, pp:724-729 [Conf]
   
8. Ivor W. Tsang, James T. Kwok, Pak-Ming Cheung
   Core Vector Machines: Fast SVM Training on Very Large Data Sets. [Citation Graph (0, 0)][DBLP]
   Journal of Machine Learning Research, 2005, v:6, n:, pp:363-392 [Journal]
   
9. Ivor W. Tsang, András Kocsor, James T. Kwok
   Simpler core vector machines with enclosing balls. [Citation Graph (0, 0)][DBLP]
   ICML, 2007, pp:911-918 [Conf]
   
10. Kai Zhang, Ivor W. Tsang, James T. Kwok
    Maximum margin clustering made practical. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:1119-1126 [Conf]
    
11. Ivor W. Tsang, James T. Kwok
    Large-Scale Sparsified Manifold Regularization. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1401-1408 [Conf]
    
12. 
    Improved Nyström low-rank approximation and error analysis. [Citation Graph (, )][DBLP]
    
    
13. 
    SimpleNPKL: simple non-parametric kernel learning. [Citation Graph (, )][DBLP]
    
    
14. 
    Domain adaptation from multiple sources via auxiliary classifiers. [Citation Graph (, )][DBLP]
    
    
15. 
    Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets. [Citation Graph (, )][DBLP]
    
    
16. 
    Domain Adaptation via Transfer Component Analysis. [Citation Graph (, )][DBLP]
    
    
17. 
    Spectral Embedded Clustering. [Citation Graph (, )][DBLP]
    
    
18. 
    Learning the Kernel in Mahalanobis One-Class Support Vector Machines. [Citation Graph (, )][DBLP]
    
    
19. 
    Extracting discriminative concepts for domain adaptation in text mining. [Citation Graph (, )][DBLP]
    
    
20. 
    Using large-scale web data to facilitate textual query based retrieval of consumer photos. [Citation Graph (, )][DBLP]
    
    
21. 
    T-IRS: textual query based image retrieval system for consumer photos. [Citation Graph (, )][DBLP]
    
    
22. 
    A Convex Method for Locating Regions of Interest with Multi-instance Learning. [Citation Graph (, )][DBLP]
    
    
23. 
    Predictive Distribution Matching SVM for Multi-domain Learning. [Citation Graph (, )][DBLP]
    
    
24. 
    A Semi-Supervised Framework for Feature Mapping and Multiclass Classification. [Citation Graph (, )][DBLP]