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Publications of Author

1. David R. Hardoon, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
   A Correlation Approach for Automatic Image Annotation. [Citation Graph (0, 0)][DBLP]
   ADMA, 2006, pp:681-692 [Conf]
   
2. Hongying Meng, John Shawe-Taylor, Sándor Szedmák, Jason D. R. Farquhar
   Support Vector Machine to Synthesise Kernels. [Citation Graph (0, 0)][DBLP]
   Deterministic and Statistical Methods in Machine Learning, 2004, pp:242-255 [Conf]
   
3. Sándor Szedmák, John Shawe-Taylor
   Synthesis of maximum margin and multiview learning using unlabeled data. [Citation Graph (0, 0)][DBLP]
   ESANN, 2006, pp:479-484 [Conf]
   
4. Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
   Learning hierarchical multi-category text classification models. [Citation Graph (0, 0)][DBLP]
   ICML, 2005, pp:744-751 [Conf]
   
5. Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc J. Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang
   The 2005 PASCAL Visual Object Classes Challenge. [Citation Graph (0, 0)][DBLP]
   MLCW, 2005, pp:117-176 [Conf]
   
6. Jason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor, Sándor Szedmák
   Two view learning: SVM-2K, Theory and Practice. [Citation Graph (0, 0)][DBLP]
   NIPS, 2005, pp:- [Conf]
   
7. Peter L. Hammer, Alexander Kogan, Bruno Simeone, Sándor Szedmák
   Pareto-optimal patterns in logical analysis of data. [Citation Graph (0, 0)][DBLP]
   Discrete Applied Mathematics, 2004, v:144, n:1-2, pp:79-102 [Journal]
   
8. Peter L. Hammer, Yanpei Liu, Bruno Simeone, Sándor Szedmák
   Saturated systems of homogeneous boxes and the logical analysis of numerical data. [Citation Graph (0, 0)][DBLP]
   Discrete Applied Mathematics, 2004, v:144, n:1-2, pp:103-109 [Journal]
   
9. Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
   Kernel-Based Learning of Hierarchical Multilabel Classification Models. [Citation Graph (0, 0)][DBLP]
   Journal of Machine Learning Research, 2006, v:7, n:, pp:1601-1626 [Journal]
   
10. David R. Hardoon, Sándor Szedmák, John Shawe-Taylor
    Canonical Correlation Analysis: An Overview with Application to Learning Methods. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:12, pp:2639-2664 [Journal]
    
11. Sándor Szedmák, John Shawe-Taylor
    Synthesis of maximum margin and multiview learning using unlabeled data. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2007, v:70, n:7-9, pp:1254-1264 [Journal]
    
12. 
    A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning. [Citation Graph (, )][DBLP]
    
    
13. 
    Kernel Regression Based Machine Translation. [Citation Graph (, )][DBLP]