Kernel Methods

Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NeurIPS 2013 Least Informative Dimensions NeurIPS 2013 Local Deep Kernel Learning for Efficient Non-linear SVM Prediction ICML 2013 Multi-Class Classification with Maximum Margin Multiple Kernel ICML 2013 Nyström Approximation for Large-Scale Determinantal Processes AISTATS 2013 On A Nonlinear Generalization of Sparse Coding and Dictionary Learning ICML 2013 Online Kernel Learning with a Near Optimal Sparsity Bound ICML 2013 On One-Shot Similarity Kernels: Explicit Feature Maps and Properties ICCV 2013 Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification ACML 2013 q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions NeurIPS 2013 Robust Low Rank Kernel Embeddings of Multivariate Distributions NeurIPS 2013 Scalable kernels for graphs with continuous attributes NeurIPS 2013 Sign Cauchy Projections and Chi-Square Kernel NeurIPS 2013 Sketching Structured Matrices for Faster Nonlinear Regression NeurIPS 2013 Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. NeurIPS 2013 Structure Discovery in Nonparametric Regression through Compositional Kernel Search ICML 2013 Supervised Kernel Descriptors for Visual Recognition CVPR 2013 Vanishing Component Analysis ICML 2013 A new metric on the manifold of kernel matrices with application to matrix geometric means NeurIPS 2012 Data dependent kernels in nearly-linear time AISTATS 2012 Ensemble weighted kernel estimators for multivariate entropy estimation NeurIPS 2012 Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space AISTATS 2012 Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness AISTATS 2012 Gradient-based kernel method for feature extraction and variable selection NeurIPS 2012 Gradient Weights help Nonparametric Regressors NeurIPS 2012