Pattern Classification, 2000. ,
Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998. ,
DOI : 10.1109/5.726791
The Nature of Statistical Learning Theory, 1995. ,
An introduction to variable and feature selection, Journal of Machine Learning Research, vol.3, pp.1157-1182, 2003. ,
Handwritten digit recognition with a back-propagation network, Advances in Neural Information Processing Systems, pp.396-404, 1990. ,
Improving the accuracy and speed of support vector machines, Advances in Neural Information Processing Systems, pp.375-381, 1997. ,
Best practices for convolutional neural networks applied to visual document analysis, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings., pp.958-962, 2003. ,
DOI : 10.1109/ICDAR.2003.1227801
Evolutionary tuning of multiple SVM parameters, Proc. of the 12th Europ. Symp. on Artificial Neural Networks (ESANN), pp.519-524, 2004. ,
DOI : 10.1016/j.neucom.2004.11.022
Choosing multiple parameters for support vector machines, Machine Learning, vol.46, issue.1/3, pp.131-159, 2002. ,
DOI : 10.1023/A:1012450327387
Optimization of the SVM Kernels Using an Empirical Error Minimization Scheme, Lecture Notes in Computer Science, vol.2388, pp.354-369, 2002. ,
DOI : 10.1007/3-540-45665-1_28
Multiclass support vector machines, 1998. ,
URL : https://hal.archives-ouvertes.fr/hal-00750277
On the algorithmic implementation of multiclass kernelbased vector machines, Journal of Machine Learning Research, vol.2, pp.265-292, 2001. ,
A new multi-class SVM based on a uniform convergence result, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, pp.183-188, 2000. ,
DOI : 10.1109/IJCNN.2000.860770
URL : https://hal.archives-ouvertes.fr/inria-00099215
Multicategory Classification by Support Vector Machines, Computational Optimization and Applications, vol.12, pp.53-79, 1999. ,
DOI : 10.1007/978-1-4615-5197-3_5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.24.3594
Combining Discriminant Models with New Multi-Class SVMs, Pattern Analysis & Applications, vol.5, issue.2, pp.168-179, 2002. ,
DOI : 10.1007/s100440200015
URL : https://hal.archives-ouvertes.fr/inria-00107869
Learning algorithms for classification: A comparison on handwritten digit recognition, Neural Networks: The Statistical Mechanics Perspective, pp.261-276, 1995. ,
The MNIST database of handwritten digits ,
Training invariant support vector machines, Machine Learning, vol.46, issue.1/3, pp.161-190, 2002. ,
DOI : 10.1023/A:1012454411458
Shape matching and object recognition using shape contexts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.4, pp.509-522, 2002. ,
DOI : 10.1109/34.993558
Analysis of errors of handwritten digits made by a multitude of classifiers, Pattern Recognition Letters, vol.26, issue.3, pp.369-379, 2005. ,
DOI : 10.1016/j.patrec.2004.10.019
Automatic verification of the outputs of multiple classifiers for unconstrained handwritten numerals, Master's thesis, 2004. ,