##### Personal tools
You are here: Home Publications

# Publications

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.

1 2 3 [4] 5 6 7 ... 15

Hsu, C and Lin, C (2001).
A Comparison on Methods for Multi-class Support Vector Machines
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.

Hua, S and Sun, Z (2001).
A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach
Journal of Molecular Biology:(in press).

Jianhua XU, XZ (2001).
Kernel Neuron and Its Training Algorithm
In: 8th International conference on neural information, vol. 2, pp. 861-866.

Ke, H and Zhang, X (2001).
Editing Support Vector Machines
Proceedings of IJCNN'01, 2:1464-1467.

Kecman, V (2001).
Learning and Soft Computing, Support Vector Machines, Neural Networks and Fuzzy Logic Models
MIT Press.

Feasible Direction Decomposition Algorithms for Training Support Vector Machines
Machine Learning.

Lee, Y, Lin, Y, and Wahba, G (2001).
Multicategory Support Vector Machines
Department of Statistics, University of Wisconsin, Madison WI.

Liao, S, Lin, H, and Lin, C (2001).
A note on the decomposition methods for support vector regression
NTU.

Lin, C (2001).
Stopping Criteria of Decomposition Methods for Support Vector Machines: a Theoretical Justification
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.

Lu, J, Plataniotis, K, and Venetsanopoulos, A (2001).
Face Recognition Using Feature Optimization and $\nu$-Support Vector Learning''
In: Proceedings of the IEEE International Workshop on Neural Networks for Signal Processing, pp. 373-382, Falmouth, MA., USA.

M\"uller, K, Mika, S, Rätsch, G, and Tsuda, K (2001).
An Introduction to Kernel-Based Learning Algorithms
IEEE Transactions on Neural Networks, 12(2):181–201.

Mangasarian, OL and Musicant, DR (2001).
Lagrangian Support Vector Machines
Journal of Machine Learning Research, 1:161–177.

Müller, K, Mika, S, Rätsch, G, Tsuda, K, and Schölkopf, B (2001).
An Introduction to Kernel-based Learning Algorithms
IEEE Neural Networks, 12(2):181–201.

Rosipal, R and Trejo, L (2001).
Kernel Partial Least Squares Regression in RKHS
CIS Department, University of Paisley, UK.

Ruiz, A and López-de-Teruel, P (2001).
Nonlinear Kernel-Based Statistical Pattern Analysis
IEEE Transactions on Neural Networks, 12(1):16-32.

Rätsch, G, Demiriz, A, and Bennett, KP (2001).
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Machine Learning Journal.

Schölkopf, B (2001).
SVM and Kernel Methods
Miscellaneous publication.

Smola, A and Bartlett, P (2001).
Sparse Greedy Gaussian Process Regression
In: Advances in Neural Information Processing Systems 13.

Smola, AJ, Mika, S, Schölkopf, B, and Williamson, RC (2001).
Regularized Principal Manifolds
Journal of Machine Learning Research.

Steinwart, I (2001).
On the influence of the kernel on the generalization ability of support vector machines
Jenaer Schriften zur Mathematik und Informatik der FSU Jena, Germany.

Steinwart, I (2001).
On the generalization ability of support vector machines
Technical Report 07-01 FSU Jena.

Suykens, J, Vandewalle, J, and Moor, BD (2001).
Optimal Control by Least Squares Support Vector Machines
Neural Networks, 14(1):23-35.

T., VG, J., S, D., B, A., L, G., L, B., V, B., DM, and J., V (2001).
Financial Time Series Prediction using Least Squares Support Vector Machines within the Evidence Framework
IEEE Transactions on Neural Networks, Special Issue on Neural Networks in Financial Engineering, 12(4):809-821.

Tresp, V (2001).
Mixtures of Gaussian Processes
In: Advances in Neural Information Processing Systems, vol. 13.

Tresp, V (2001).
Scaling Kernel-Based Systems to Large Data Sets
Data Mining and Knowledge Discovery, 5(3):197-211.

1 2 3 [4] 5 6 7 ... 15