kernel methods

On Kernelized Multi-armed Bandits ICML 2017 Online Asymmetric Similarity Learning for Cross-Modal Retrieval CVPR 2017 On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks NeurIPS 2017 Recursive Sampling for the Nystrom Method NeurIPS 2017 Reliably Learning the ReLU in Polynomial Time COLT 2017 Robust Hypothesis Test for Nonlinear Effect with Gaussian Processes NeurIPS 2017 Sliced Wasserstein Kernel for Persistence Diagrams ICML 2017 Spatial Decompositions for Large Scale SVMs AISTATS 2017 Spectral Mixture Kernels for Multi-Output Gaussian Processes NeurIPS 2017 Variational Inference for Gaussian Process Models with Linear Complexity NeurIPS 2017 A Kernelized Stein Discrepancy for Goodness-of-fit Tests ICML 2016 A Kernel Test of Goodness of Fit ICML 2016 A Nonlinear Regression Technique for Manifold Valued Data With Applications to Medical Image Analysis CVPR 2016 Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification CVPR 2016 A Probabilistic Programming Approach To Probabilistic Data Analysis NeurIPS 2016 Back to the Future: Radial Basis Function Networks Revisited AISTATS 2016 Bayesian Nonparametric Kernel-Learning AISTATS 2016 Bayesian optimization for automated model selection NeurIPS 2016 Bayesian optimization for automated model selection AutoML 2016 Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation NeurIPS 2016 Compact Bilinear Pooling CVPR 2016 Computationally Efficient Nyström Approximation using Fast Transforms ICML 2016 Conditional Generative Moment-Matching Networks NeurIPS 2016 Deep SimNets CVPR 2016 Discriminative Embeddings of Latent Variable Models for Structured Data ICML 2016