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Computation with infinite neural networks [1%] by admin, 2007-01-31 11:09
Gaussian processes for regression [1%] by admin, 2007-01-31 11:09
Computing with infinite networks [1%] by admin, 2007-01-31 11:09
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo [1%] by admin, 2007-01-31 11:09
A Geometric Approach to Train Support Vector Machines [1%] by admin, 2007-01-31 11:09
Sparse Greedy Gaussian Process Regression [1%] by admin, 2007-01-31 11:09
Kernel Principal Component Regression with EM Approach to Nonlinear Principal Components Extraction. [1%] by admin, 2007-01-31 11:09
In kernel based methods such as Support Vector Machines, Kernel PCA, Gaussian Processes or Regularization Networks the computational requirements scale ...
A note on the decomposition methods for support vector regression [1%] by admin, 2007-01-31 11:09
The dual formulation of support vector regression involves with two closely related sets of variables. When the decomposition method is used, many ...
Learning and Soft Computing, Support Vector Machines, Neural Networks and Fuzzy Logic Models [1%] by admin, 2007-01-31 11:09
This is the first textbook that provides a thorough, comprehensive and unified introduction to the field of learning from experimental data and soft ...
Incremental and Decremental Support Vector Machine Learning [1%] by admin, 2007-01-31 11:09
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the Kuhn-Tucker ...
A Bayesian Committee Machine [1%] by admin, 2007-01-31 11:09
The Bayesian committee machine (BCM) is a novel approach to combining estimators which were trained on different data sets. Although the BCM can be ...
The Generalized Bayesian Committee Machine [1%] by admin, 2007-01-31 11:09
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used ...
Mixtures of Gaussian Processes [1%] by admin, 2007-01-31 11:09
We introduce the mixture of Gaussian processes (MGP) model which is useful for applications in which the optimal bandwidth of a map is input dependent. ...
Generalization properties of finite-size polynomial support vector machines [1%] by admin, 2007-01-31 11:09
On the influence of the kernel on the generalization ability of support vector machines [1%] by admin, 2007-01-31 11:09
In this article we study the generalization abilities of several classifiers of support vector machine type. Our considerations are based on an ...
A Spin-Glass Markov Random Field for 3-D Object Recognition [1%] by admin, 2007-01-31 11:09
Target Detection in Radar Imagery using Support Vector Machines with Training Size Biasing [1%] by admin, 2007-01-31 11:09
Dual nu-Support Vector Machine with Error Rate and Training Size Biasing [1%] by admin, 2007-01-31 11:09
Mercer Kernel Based Clustering in Feature Space [1%] by admin, 2007-01-31 11:09
This paper presents a method for both the unsupervised partitioning of a sample of data and the estimation of the possible number of inherent clusters ...
Mercer Kernel Based Clustering in Feature Space [1%] by admin, 2007-01-31 11:09
This paper presents a method for both the unsupervised partitioning of a sample of data and the estimation of the possible number of inherent clusters ...
SVMTorch: Support Vector Machines for Large-Scale Regression Problems [1%] by admin, 2007-01-31 11:09
Support Vectors Selection by Linear Programming [1%] by admin, 2007-01-31 11:09
A linear programming (LP) based method is proposed for learning from experimental data in solving the nonlinear regression and classification problems. ...
Kernel Partial Least Squares Regression in RKHS [1%] by admin, 2007-01-31 11:09
A family of regularized least squares regression models in a Reproducing Kernel Hilbert Space is extended by the Kernel Partial Least Squares (PLS) ...
Lagrangian Support Vector Machines [1%] by admin, 2007-01-31 11:09
Feasible Direction Decomposition Algorithms for Training Support Vector Machines [1%] by admin, 2007-01-31 11:09
The article presents a general view of a class of decomposition algorithms for training Support Vector Machines (SVM) which are motivated by the method ...
A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach [1%] by admin, 2007-01-31 11:09
We introduced a new method of protein secondary structure prediction which is based on the theory of Support Vector Machine (SVM). SVM represents a new ...
Linear Programming Boosting via Column Generation [1%] by admin, 2007-01-31 11:09
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces [1%] by admin, 2007-01-31 11:09
A Column Generation Algorithm for Boosting [1%] by admin, 2007-01-31 11:09
Optimization Approaches to Semi-supervised Learning [1%] by admin, 2007-01-31 11:09

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