reproducing kernel hilbert space

Learning structured densities via infinite dimensional exponential families NeurIPS 2015 Learning with Group Invariant Features: A Kernel Perspective. NeurIPS 2015 Modelling Policies in MDPs in Reproducing Kernel Hilbert Space AISTATS 2015 Predicting the Future Behavior of a Time-Varying Probability Distribution CVPR 2015 Revisiting Kernelized Locality-Sensitive Hashing for Improved Large-Scale Image Retrieval CVPR 2015 Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering AISTATS 2015 Statistical Topological Data Analysis - A Kernel Perspective NeurIPS 2015 Two-stage sampled learning theory on distributions AISTATS 2015 Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule JMLR 2014 Kernel Adaptive Metropolis-Hastings ICML 2014 Kernel Mean Estimation and Stein Effect ICML 2014 Kernel Mean Estimation via Spectral Filtering NeurIPS 2014 Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces NeurIPS 2014 Margins, Kernels and Non-linear Smoothed Perceptrons ICML 2014 Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection ICML 2014 Recovering Distributions from Gaussian RKHS Embeddings AISTATS 2014 Scalable Kernel Methods via Doubly Stochastic Gradients NeurIPS 2014 Simultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction CVPR 2014 Theoretical Analyses on Ensemble and Multiple Kernel Regressors ACML 2014 A Kernel Test for Three-Variable Interactions NeurIPS 2013 A unifying framework for vector-valued manifold regularization and multi-view learning ICML 2013 Consistency of Robust Kernel Density Estimators COLT 2013 Differential Privacy for Functions and Functional Data JMLR 2013 Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels JMLR 2013 Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NeurIPS 2013