hilbert space

A Unifying View of Representer Theorems ICML 2014 Bregman Divergences for Infinite Dimensional Covariance Matrices CVPR 2014 Learning Euclidean-to-Riemannian Metric for Point-to-Set Classification CVPR 2014 Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces NeurIPS 2014 Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space NeurIPS 2014 Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space NeurIPS 2014 Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations COLT 2014 Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels ICML 2013 Fastfood - Computing Hilbert Space Expansions in loglinear time ICML 2013 Ultrahigh Dimensional Feature Screening via RKHS Embeddings AISTATS 2013 Kernel Topic Models AISTATS 2012 Perceptron Learning of SAT NeurIPS 2012 The representer theorem for Hilbert spaces: a necessary and sufficient condition NeurIPS 2012 Learning a Robust Relevance Model for Search Using Kernel Methods JMLR 2011 Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NeurIPS 2011 Distribution Matching for Transduction NeurIPS 2009 Refinement of Reproducing Kernels JMLR 2009 Universal Kernel-Based Learning with Applications to Regular Languages JMLR 2009 Learning Similarity with Operator-valued Large-margin Classifiers JMLR 2008 Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NeurIPS 2006