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Kernel Methods

642 papers

Papers per year

9
23
20
31
19
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Papers

Supervised Learning with Tensor Networks NIPS 2016
Orthogonal Random Features NIPS 2016
The Multiscale Laplacian Graph Kernel NIPS 2016
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NIPS 2016
Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning NIPS 2016
On Robustness of Kernel Clustering NIPS 2016
Error Analysis of Generalized Nyström Kernel Regression NIPS 2016
Multiple Kernel Learning with Data Augmentation ACML 2016
Cost Sensitive Online Multiple Kernel Classification ACML 2016
Random Fourier Features For Operator-Valued Kernels ACML 2016
Streaming Kernel Principal Component Analysis AISTATS 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
Persistence weighted Gaussian kernel for topological data analysis ICML 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
On Quantile Regression in Reproducing Kernel Hilbert Spaces with the Data Sparsity Constraint JMLR 2016
Large Scale Online Kernel Learning JMLR 2016
Kernel Mean Shrinkage Estimators JMLR 2016
SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions JMLR 2016