Kernel Methods

Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification IJCAI 2018 Statistical and Computational Trade-Offs in Kernel K-Means NeurIPS 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NeurIPS 2018 Streaming kernel regression with provably adaptive mean, variance, and regularization JMLR 2018 The Weighted Kendall and High-order Kernels for Permutations ICML 2018 Zero-Shot Kernel Learning CVPR 2018 Adapting Kernel Representations Online Using Submodular Maximization ICML 2017 A General Framework for Curve and Surface Comparison and Registration With Oriented Varifolds CVPR 2017 A Linear-Time Kernel Goodness-of-Fit Test NeurIPS 2017 An Empirical Study on The Properties of Random Bases for Kernel Methods NeurIPS 2017 Asymmetric Feature Maps With Application to Sketch Based Retrieval CVPR 2017 Data Augmentation, Missing Feature Mask and Kernel Classification for Through-the-Wall Acoustic Surveillance Interspeech 2017 Data-driven Random Fourier Features using Stein Effect IJCAI 2017 Deep Learning in Semantic Kernel Spaces ACL 2017 Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning ACL 2017 Distributed Learning with Regularized Least Squares JMLR 2017 Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017 Diving into the shallows: a computational perspective on large-scale shallow learning NeurIPS 2017 Efficient Kernel Selection via Spectral Analysis IJCAI 2017 FALKON: An Optimal Large Scale Kernel Method NeurIPS 2017 Gaussian Quadrature for Kernel Features NeurIPS 2017 Generative Local Metric Learning for Kernel Regression NeurIPS 2017 Kernel Feature Selection via Conditional Covariance Minimization NeurIPS 2017 Kernelized Support Tensor Machines ICML 2017 Kernel Square-Loss Exemplar Machines for Image Retrieval CVPR 2017