kernel methods

Localized Incomplete Multiple Kernel k-means IJCAI 2018 Multi-Scale Location-Aware Kernel Representation for Object Detection CVPR 2018 Multi-view Metric Learning in Vector-valued Kernel Spaces AISTATS 2018 Neural Tangent Kernel: Convergence and Generalization in Neural Networks NeurIPS 2018 Non-Linear Temporal Subspace Representations for Activity Recognition CVPR 2018 On Fast Leverage Score Sampling and Optimal Learning NeurIPS 2018 On gradient regularizers for MMD GANs NeurIPS 2018 Online Kernel Selection via Incremental Sketched Kernel Alignment IJCAI 2018 On the Spectrum of Random Features Maps of High Dimensional Data ICML 2018 Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods ICML 2018 Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate NeurIPS 2018 Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams NeurIPS 2018 Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions EMNLP 2018 Post Selection Inference with Kernels AISTATS 2018 Quadrature-based features for kernel approximation NeurIPS 2018 Random Warping Series: A Random Features Method for Time-Series Embedding AISTATS 2018 Relating Leverage Scores and Density using Regularized Christoffel Functions NeurIPS 2018 RetGK: Graph Kernels based on Return Probabilities of Random Walks NeurIPS 2018 Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification IJCAI 2018 Solving lp-norm regularization with tensor kernels AISTATS 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NeurIPS 2018 Stein Points ICML 2018 Stein Variational Gradient Descent as Moment Matching NeurIPS 2018 Stein Variational Gradient Descent Without Gradient ICML 2018 Structured Gaussian Processes with Twin Multiple Kernel Learning ACML 2018