Kernel Methods

To go deep or wide in learning? AISTATS 2014 Video Motion Segmentation Using New Adaptive Manifold Denoising Model CVPR 2014 Adaptivity to Local Smoothness and Dimension in Kernel Regression NeurIPS 2013 A Kernel Test for Three-Variable Interactions NeurIPS 2013 An Adaptive Descriptor Design for Object Recognition in the Wild ICCV 2013 Analyzing the Harmonic Structure in Graph-Based Learning NeurIPS 2013 Anchored Neighborhood Regression for Fast Example-Based Super-Resolution ICCV 2013 Approximate Inference in Continuous Determinantal Processes NeurIPS 2013 A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning ICML 2013 A unifying framework for vector-valued manifold regularization and multi-view learning ICML 2013 B-test: A Non-parametric, Low Variance Kernel Two-sample Test NeurIPS 2013 Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment ICML 2013 Characterizing the Representer Theorem ICML 2013 Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach ICCV 2013 Consistency of Robust Kernel Density Estimators COLT 2013 Correlated random features for fast semi-supervised learning NeurIPS 2013 Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels ICML 2013 Cross-View Action Recognition via a Continuous Virtual Path CVPR 2013 Differentially Private Learning with Kernels ICML 2013 Directed Acyclic Graph Kernels for Action Recognition ICCV 2013 Fastfood - Computing Hilbert Space Expansions in loglinear time ICML 2013 Inverse Density as an Inverse Problem: the Fredholm Equation Approach NeurIPS 2013 JKernelMachines: A Simple Framework for Kernel Machines JMLR 2013 Kernel Learning for Extrinsic Classification of Manifold Features CVPR 2013 Learning Kernels Using Local Rademacher Complexity NeurIPS 2013