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Kernel Methods

571 directly classified papers

Papers per year

Papers

Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels JMLR 2016
Optimal Learning Rates for Localized SVMs JMLR 2016
Fast DPP Sampling for Nystrom with Application to Kernel Methods ICML 2016
Recycling Randomness with Structure for Sublinear time Kernel Expansions ICML 2016
Preconditioning Kernel Matrices ICML 2016
Efficient Temporal Sequence Comparison and Classification Using Gram Matrix Embeddings on a Riemannian Manifold CVPR 2016
Robust Visual Place Recognition With Graph Kernels CVPR 2016
Kernel Approximation via Empirical Orthogonal Decomposition for Unsupervised Feature Learning CVPR 2016
Sliced Wasserstein Kernels for Probability Distributions CVPR 2016
Random Features for Sparse Signal Classification CVPR 2016
Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation CVPR 2016
Conditional Generative Moment-Matching Networks NIPS 2016
On Valid Optimal Assignment Kernels and Applications to Graph Classification NIPS 2016
Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis NIPS 2016
Bayesian optimization for automated model selection NIPS 2016
Dual Space Gradient Descent for Online Learning NIPS 2016
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels NIPS 2016
Supervised Learning with Tensor Networks NIPS 2016
The Multiscale Laplacian Graph Kernel NIPS 2016
Modelling Policies in MDPs in Reproducing Kernel Hilbert Space AISTATS 2015
A Structural Smoothing Framework For Robust Graph Comparison NIPS 2015
Spherical Random Features for Polynomial Kernels NIPS 2015
Less is More: Nyström Computational Regularization NIPS 2015
Halting in Random Walk Kernels NIPS 2015
The Kendall and Mallows Kernels for Permutations ICML 2015