Regularization and statistical learning theory for data analysis
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Massimiliano Pontil | Alessandro Verri | Theodoros Evgeniou | Tomaso Poggio | A. Verri | T. Poggio | M. Pontil | T. Evgeniou
[1] Federico Girosi,et al. An improved training algorithm for support vector machines , 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.
[2] László Györfi,et al. A Probabilistic Theory of Pattern Recognition , 1996, Stochastic Modelling and Applied Probability.
[3] Tomaso A. Poggio,et al. Pedestrian detection using wavelet templates , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[4] ScienceDirect. Computational statistics & data analysis , 1983 .
[5] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[6] Vladimir Vapnik,et al. Chervonenkis: On the uniform convergence of relative frequencies of events to their probabilities , 1971 .
[7] J. Platt. Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .
[8] Noga Alon,et al. Scale-sensitive dimensions, uniform convergence, and learnability , 1997, JACM.
[9] Alessandro Verri,et al. Learning to Recognize Visual Dynamic Events from Examples , 2000, International Journal of Computer Vision.
[10] Tomaso A. Poggio,et al. A general framework for object detection , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).
[11] Tomaso A. Poggio,et al. Regularization Theory and Neural Networks Architectures , 1995, Neural Computation.
[12] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[13] V. A. Morozov,et al. Methods for Solving Incorrectly Posed Problems , 1984 .
[14] Massimiliano Pontil,et al. Support Vector Machines for 3D Object Recognition , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[15] Emanuele Trucco,et al. Visual Learning of Weight from Shape Using Support Vector Machines , 1998, BMVC.
[16] Robert E. Schapire,et al. Efficient distribution-free learning of probabilistic concepts , 1990, Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.
[17] A. N. Tikhonov,et al. Solutions of ill-posed problems , 1977 .
[18] Emanuele Trucco,et al. A trainable system for grading fish from images , 2001, Appl. Artif. Intell..
[19] Tomaso Poggio,et al. A Unified Framework for Regularization Networks and Support Vector Machines , 1999 .
[20] L. Galway. Spline Models for Observational Data , 1991 .