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by admin last modified 2008-11-11 09:39
Publications in the database on Kernel-Machines.Org

This folder holds the following references to publications, sorted by year and author.

There are 357 references in this bibliography folder.

Smola, A, Sch\"olkopf, B, and M\"uller, K (1998).
General cost functions for Support Vector Regression
In: Proc. of the Ninth Australian Conf. on Neural Networks, ed. by T. Downs and M. Frean and M. Gallagher, pp. 79 - 83, Brisbane, Australia, University of Queensland.

Smola, AJ (1998).
Learning with Kernels
PhD thesis, Technische Universität Berlin.

Smola, AJ and Schölkopf, B (1998).
On a Kernel–based Method for Pattern Recognition, Regression, Approximation and Operator Inversion
Algorithmica, 22:211–231.

Smola, AJ and Schölkopf, B (1998).
From Regularization Operators to Support Vector Kernels
In: Advances in Neural information processings systems 10, pp. 343–349, San Mateo, CA.

Smola, AJ and Schölkopf, B (1998).
A Tutorial on Support Vector Regression
Royal Holloway College, NeuroCOLT Technical Report(NC-TR-98-030), University of London, UK.

Smola, AJ, Frieß, T, and Schölkopf, B (1998).
Semiparametric Support Vector and Linear Programming Machines
In: Advances in Neural Information Processing Systems, 11, MIT Press.

Smola, AJ, Schölkopf, B, and Müller, K (1998).
The Connection between Regularization Operators and Support Vector Kernels
Neural Networks, 11:637–649.

Smola, AJ, Williamson, RC, and Schölkopf, B (1998).
Generalization Bounds for Convex Combinations of Kernel Functions
Royal Holloway College, NeuroCOLT Technical Report(NC-TR-98-022), University of London, UK.

Street, WN and Mangasarian, OL (1998).
Improved Generalization via Tolerant Training
Journal of Optimization Theory and Applications, 96:259-279.

Williams, CK (1998).
Prediction with Gaussian Processes: From Linear Regression to Linear Prediction and beyond
In: Learning in Graphical Models, ed. by Jordan, M. I., pp. 599-621, Kluwer Academic.

Williams, CK (1998).
Computation with infinite neural networks
Neural Computation, 10(5):1203-1216.

Williams, CK and Barber, D (1998).
Bayesian classification with Gaussian processes
IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(12):1342-1351.

Williamson, RC, Smola, AJ, and Schölkopf, B (1998).
Generalization Performance of Regularization Networks and Support Vector Machines via Entropy Numbers of Compact Operators
Royal Holloway College, NeuroCOLT Technical Report(NC-TR-98-019), University of London, UK.

Zhu, H, Williams, CK, Rohwer, RJ, and Morciniec, M (1998).
Gaussian regression and optimal finite dimensional linear models
In: Neural Networks and Machine Learning, ed. by C. M. Bishop, Springer-Verlag, Berlin.

Barber, D and Williams, CK (1997).
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo
In: Advances in Neural Information Processing Systems 9, ed. by Mozer, M. C. and Jordan, M. I. and Petsche, T., MIT Press.

Bennett, KP and Blue, JA (1997).
A Support Vector Machine Approach to Decision Trees
In: Proceedings of IJCNN'98, pp. 2396–2401, Anchorage, Alaska.

Burges, CJ and Schölkopf, B (1997).
Improving the accuracy and speed of support vector learning machines
In: Advances in Neural Information Processing Systems 9, ed. by M. Mozer and M. Jordan and T. Petsche, pp. 375–381, Cambridge, MA, MIT Press.

Drucker, H, Burges, CJ, Kaufman, L, Smola, A, and Vapnik, V (1997).
Support vector regression machines
In: Advances in Neural Information Processing Systems 9, ed. by M. Mozer and M. Jordan and T. Petsche, pp. 155–161, Cambridge, MA, MIT Press.

MacKay, D (1997).
Introduction to Gaussian Processes
Miscellaneous publication.

Mukherjee, S, Osuna, E, and Girosi, F (1997).
Nonlinear Prediction of Chaotic Time Series using a Support Vector Machine
In: Neural Networks for Signal Processing VII — Proceedings of the 1997 IEEE Workshop, ed. by J. Principe and L. Gile and N. Morgan and E. Wilson, New York, IEEE.

Neal, R (1997).
Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification
University of Toronto, Dept. of Computer Science.

Oren, M, Papageorgiou, C, Sinha, P, and Osuna, E (1997).
Pedestrian Detection Using Wavelet Templates
In: Proceedings of CVPR'97, Puerto Rico.

Osuna, E, Freund, R, and Girosi, F (1997).
Training Support Vector Machines: An Application to Face Detection
In: Proceedings of CVPR'97, Puerto Rico.

Osuna, E, Freund, R, and Girosi, F (1997).
An Improved Training Algorithm for Support Vector Machines
In: Neural Networks for Signal Processing VII — Proceedings of the 1997 IEEE Workshop, ed. by J. Principe and L. Gile and N. Morgan and E. Wilson, pp. 276 - 285, New York, IEEE.

Pontil, M and Verri, A (1997).
Properties of Support Vector Machines
Neural Computation, 10:955–974.

 

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