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On Kernel-Target Alignment

Authors: Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola - Conference on Neural Information Processing Systems, NeurIPS 2001 cited by 1,241

On the method of boundeddifferencesOn the method of bounded differencesPartitioning SparseMatrices with…Partitioning Sparse Matrices with Eigenvectors of GraphsA Probabilistic Theoryof Pattern RecognitionA Probabilistic Theory of Pattern RecognitionStructural RiskMinimization Over…Structural Risk Minimization Over Data-Dependent HierarchiesAdvances in kernelmethods: support vector…Advances in kernel methods: support vector learningAn Introduction toSupport Vector Machines…An Introduction to Support Vector Machines and Other Kernel-based Learning MethodsAn Introduction toSupport Vector MachinesAn Introduction to Support Vector MachinesLearning with KernelsLearning with KernelsGene functionalclassification from…Gene functional classification from heterogeneous dataLearning from Labeledand Unlabeled Data usin…Learning from Labeled and Unlabeled Data using Graph MincutsLearning KernelClassifiersLearning Kernel ClassifiersLearning the KernelMatrix with…Learning the Kernel Matrix with Semi-Definite ProgrammingLearning the KernelMatrix with…Learning the Kernel Matrix with Semi-Definite ProgrammingFeature Selection forSupport Vector Machines…Feature Selection for Support Vector Machines by Means of Genetic AlgorithmsWord-Sequence KernelsWord-Sequence KernelsOptimal kernel selectionin Kernel Fisher…Optimal kernel selection in Kernel Fisher discriminant analysisSemi-Supervised Learning(Adaptive Computation…Semi-Supervised Learning (Adaptive Computation and Machine Learning)Learning TheDiscriminative…Learning The Discriminative Power-Invariance Trade-OffMultiway SpectralClustering with…Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCAMultitask Sparsity viaMaximum Entropy…Multitask Sparsity via Maximum Entropy DiscriminationAn overview of kernelalignment and its…An overview of kernel alignment and its applicationsRepresentative MultipleKernel Learning for…Representative Multiple Kernel Learning for Classification in Hyperspectral ImageryEvaluation measures forkernel optimizationEvaluation measures for kernel optimizationNonlinear MultipleKernel Learning With…Nonlinear Multiple Kernel Learning With Multiple-Structure-Element Extended Morphological Profiles for Hyperspectral Image ClassificationOn Kernel-TargetAlignmentOn Kernel-Target AlignmentEarlier referencesFocus paperCiting papersOlderNewer

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