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Kernel Methods

73 papers

Papers per year

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Papers

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