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Kernel Methods

73 directly classified papers

Papers per year

Papers

Modelling Policies in MDPs in Reproducing Kernel Hilbert Space AISTATS 2015
Geodesic Exponential Kernels: When Curvature and Linearity Conflict CVPR 2015
Two-stage sampled learning theory on distributions AISTATS 2015
Human Action Recognition Based on Context-Dependent Graph Kernels CVPR 2014
Fast Kernel Learning for Multidimensional Pattern Extrapolation NIPS 2014
JKernelMachines: A Simple Framework for Kernel Machines JMLR 2013
Adaptivity to Local Smoothness and Dimension in Kernel Regression NIPS 2013
Inverse Density as an Inverse Problem: the Fredholm Equation Approach NIPS 2013
The representer theorem for Hilbert spaces: a necessary and sufficient condition NIPS 2012
Kernel Hyperalignment NIPS 2012
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NIPS 2011
Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions NIPS 2010
A Fast, Consistent Kernel Two-Sample Test NIPS 2009
Fast subtree kernels on graphs NIPS 2009
Learning Non-Linear Combinations of Kernels NIPS 2009
Diffeomorphic Dimensionality Reduction NIPS 2008
Bayesian Network Score Approximation using a Metagraph Kernel NIPS 2008
Deep Learning with Kernel Regularization for Visual Recognition NIPS 2008
Kernel Measures of Conditional Dependence NIPS 2007
A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems NIPS 2006
Active learning for misspecified generalized linear models NIPS 2006
Gaussian and Wishart Hyperkernels NIPS 2006
Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NIPS 2006