Kernel Methods

Layer-wise analysis of deep networks with Gaussian kernels NeurIPS 2010 Learning Kernels with Radiuses of Minimum Enclosing Balls NeurIPS 2010 Learning Nonlinear Dynamic Models from Non-sequenced Data AISTATS 2010 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NeurIPS 2010 Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NeurIPS 2010 Multiple Kernel Learning and the SMO Algorithm NeurIPS 2010 Nonlinear functional regression: a functional RKHS approach AISTATS 2010 Nonparametric Tree Graphical Models AISTATS 2010 Online Passive-Aggressive Algorithms on a Budget AISTATS 2010 On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010 On the relation between universality, characteristic kernels and RKHS embedding of measures AISTATS 2010 Optimal learning rates for Kernel Conjugate Gradient regression NeurIPS 2010 Scrambled Objects for Least-Squares Regression NeurIPS 2010 Spectral Regularization for Support Estimation NeurIPS 2010 The Feature Selection Path in Kernel Methods AISTATS 2010 Universal Consistency of Multi-Class Support Vector Classification NeurIPS 2010 Universal Kernels on Non-Standard Input Spaces NeurIPS 2010 Unsupervised Kernel Dimension Reduction NeurIPS 2010 Accurate rough terrain estimation with space-carving kernels RSS 2009 A Fast, Consistent Kernel Two-Sample Test NeurIPS 2009 Analysis of SVM with Indefinite Kernels NeurIPS 2009 Distribution Matching for Transduction NeurIPS 2009 Efficient and Accurate Lp-Norm Multiple Kernel Learning NeurIPS 2009 Efficient Match Kernel between Sets of Features for Visual Recognition NeurIPS 2009 Efficient Recovery of Jointly Sparse Vectors NeurIPS 2009