kernel methods

Kernel Stein Tests for Multiple Model Comparison NeurIPS 2019 Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction CoRL 2019 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NeurIPS 2019 Large-Margin Classification in Hyperbolic Space AISTATS 2019 Learning Invariant Representations with Kernel Warping AISTATS 2019 Learning metrics for persistence-based summaries and applications for graph classification NeurIPS 2019 Learning One-hidden-layer Neural Networks under General Input Distributions AISTATS 2019 Maximum Mean Discrepancy Gradient Flow NeurIPS 2019 Minimum Stein Discrepancy Estimators NeurIPS 2019 Multiple Empirical Kernel Learning with Discriminant Locality Preservation ACML 2019 Multiplicative local linear hazard estimation and best one-sided cross-validation JMLR 2019 Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction EMNLP 2019 On Exact Computation with an Infinitely Wide Neural Net NeurIPS 2019 On Lazy Training in Differentiable Programming NeurIPS 2019 Online High Rank Matrix Completion CVPR 2019 Online Learning in Kernelized Markov Decision Processes AISTATS 2019 Online learning with kernel losses ICML 2019 On the Inductive Bias of Neural Tangent Kernels NeurIPS 2019 Parsimonious Online Learning with Kernels via Sparse Projections in Function Space JMLR 2019 Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior AISTATS 2019 Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization IJCAI 2019 Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics JMLR 2019 Random Feature Maps for the Itemset Kernel AAAI 2019 Recurrent Kernel Networks NeurIPS 2019 Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel NeurIPS 2019