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**837 items matching your criteria.**

- Combining Support Vector and Mathematical Programming Methods for Induction [1%] by admin, 2007-01-31 11:07
- Geometry and Invariance in Kernel Based Methods [1%] by admin, 2007-01-31 11:07
- Bayesian Voting Schemes and Large Margin Classifiers [1%] by admin, 2007-01-31 11:07
- Making Large–Scale SVM Learning Practical [1%] by admin, 2007-01-31 11:07
- Solving the Quadratic Programming problem arising in Support Vector classification [1%] by admin, 2007-01-31 11:07
- Pairwise Classification and Support Vector Machines [1%] by admin, 2007-01-31 11:07
- Support Vector Machines for Dynamic Reconstruction of a Chaotic System [1%] by admin, 2007-01-31 11:07
- Predicting Time Series with Support Vector Machines [1%] by admin, 2007-01-31 11:07
- SV regression with epsilon-insensitive and Huber loss functions. Experimental results on time-series prediction (Mackey-Glass and Santa Fe competition ...
- On the Annealed VC Entropy for Margin Classifiers: A Statistical Mechanics Study [1%] by admin, 2007-01-31 11:07
- Reducing the Run-time Complexity in Support Vector Regression [1%] by admin, 2007-01-31 11:07
- Fast Training of Support Vector Machines using Sequential Minimal Optimization [1%] by admin, 2007-01-31 11:07
- Kernel Principal Component Analysis [1%] by admin, 2007-01-31 11:07
- Support Vector Regression with ANOVA Decomposition Kernels [1%] by admin, 2007-01-31 11:07
- Three Remarks on the Support Vector Method of Function Estimation [1%] by admin, 2007-01-31 11:07
- Support Vector Machines, Reproducing Kernel Hilbert Spaces and the Randomized GACV [1%] by admin, 2007-01-31 11:07
- Support Vector Density Estimation [1%] by admin, 2007-01-31 11:07
- Entropy numbers, operators and support vector kernels [1%] by admin, 2007-01-31 11:07
- Pattern Recognition using Generalized Portrait Method [1%] by admin, 2007-01-31 11:07
- This is the first paper on Support Vector type algorithms.
- Linear and Nonlinear Separation of Patterns by Linear Programming [1%] by admin, 2007-01-31 11:07
- Linear and nonlinear separation of two point sets in n-dimensional space is formulated as a linear programming problem, whenever the nonlinear ...
- Multi-Surface Method of Pattern Separation [1%] by admin, 2007-01-31 11:07
- Two point sets in n-dimensional space are separated by a sequence of parallel planes. Each pair of planes separates portions of the two sets while ...
- A correspondence between Bayesan estimation on stochastic processes and smoothing by splines [1%] by admin, 2007-01-31 11:07
- Some results on Tchebycheffian spline functions. [1%] by admin, 2007-01-31 11:07
- Kimeldorf and Wahba's Lemma 6.1 on variational problems in reproducing kernel spaces with linear inequality constraints is highly relevant to modern ...
- A note on one class of perceptrons [1%] by admin, 2007-01-31 11:07
- Theory of Pattern Recognition [in Russian] [1%] by admin, 2007-01-31 11:07
- In these two books, the original "Generalized Portrait" Algorithm for constructing separating hyperplanes with optimal margin is described.
- Spline Models for Observational Data [1%] by admin, 2007-01-31 11:07
- This book is about mostly multivariate function estimation in reproducing kernel Hilbert spaces. Sections 9.4 and 9.5 on inequality constraints are ...
- A Training Algorithm for Optimal Margin Classifiers [1%] by admin, 2007-01-31 11:07
- A training algorithm that maximizes the margin between the training patterns and the decision boundary is presented. The technique is applicable to a ...
- Robust Linear Programming Discrimination of Two Linearly Inseparable Sets [1%] by admin, 2007-01-31 11:07
- First occurence of the soft margin loss function.
- Automatic Capacity Tuning of Very Large VC-Dimension Classifiers [1%] by admin, 2007-01-31 11:07
- Large VC-dimension classifiers can learn difficult tasks, but are usually impractical because they generalize well only if they are trained with huge ...
- Writer adaptation for on-line handwritten character recognition. [1%] by admin, 2007-01-31 11:07
- A TDNN without its last layer serves as a preprocessor to an SVM classifier, that is retrained to peculiar writing styles. This combination allows for ...
- Support Vector Networks [1%] by admin, 2007-01-31 11:07
- In this paper, the optimal margin algorithm is generalized to non-separable problems by the introduction of slack variables in the statement of the ...