conftrace_
← Core Methods
Machine Learning › Core Methods ›

Kernel Methods

642 papers

Papers per year

9
23
20
31
19
'05
'10
'15
'20
'25

Papers

Gradient-based kernel method for feature extraction and variable selection NIPS 2012
Non-parametric Approximate Dynamic Programming via the Kernel Method NIPS 2012
The Lovász ϑ function, SVMs and finding large dense subgraphs NIPS 2012
Ensemble weighted kernel estimators for multivariate entropy estimation NIPS 2012
A new metric on the manifold of kernel matrices with application to matrix geometric means NIPS 2012
Learning from Distributions via Support Measure Machines NIPS 2012
Kernel Latent SVM for Visual Recognition NIPS 2012
Semantic Kernel Forests from Multiple Taxonomies NIPS 2012
Learning Networks of Heterogeneous Influence NIPS 2012
Optimal kernel choice for large-scale two-sample tests NIPS 2012
The representer theorem for Hilbert spaces: a necessary and sufficient condition NIPS 2012
Perceptron Learning of SAT NIPS 2012
Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging NIPS 2012
Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space AISTATS 2012
Random Feature Maps for Dot Product Kernels AISTATS 2012
Data dependent kernels in nearly-linear time AISTATS 2012
Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness AISTATS 2012
Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach AISTATS 2012
PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers NIPS 2011
Metric Learning with Multiple Kernels NIPS 2011
A Non-Parametric Approach to Dynamic Programming NIPS 2011
Optimal learning rates for least squares SVMs using Gaussian kernels NIPS 2011
Kernel Bayes' Rule NIPS 2011
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NIPS 2011