kernel methods

Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks NeurIPS 2020 Kernel Methods for Cooperative Multi-Agent Contextual Bandits ICML 2020 Kernel Methods Through the Roof: Handling Billions of Points Efficiently NeurIPS 2020 Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization AISTATS 2020 Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes RSS 2020 Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity NeurIPS 2020 Learning Data-adaptive Non-parametric Kernels JMLR 2020 Learning Kernel Tests Without Data Splitting NeurIPS 2020 Learning Over-Parametrized Two-Layer Neural Networks beyond NTK COLT 2020 Learning to Learn Kernels with Variational Random Features ICML 2020 Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces NeurIPS 2020 Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions NeurIPS 2020 More Powerful Selective Kernel Tests for Feature Selection AISTATS 2020 Morphism-Based Learning for Structured Data AAAI 2020 Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling ICML 2020 Near-linear time Gaussian process optimization with adaptive batching and resparsification ICML 2020 Neural Kernels Without Tangents ICML 2020 Nonparametric Score Estimators ICML 2020 Non-separable Non-stationary random fields ICML 2020 On 1/n neural representation and robustness NeurIPS 2020 Online Multitask Learning with Long-Term Memory NeurIPS 2020 Online Non-Convex Optimization with Imperfect Feedback NeurIPS 2020 On lp-Support Vector Machines and Multidimensional Kernels JMLR 2020 On the Expressive Power of Kernel Methods and the Efficiency of Kernel Learning by Association Schemes ALT 2020 On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels COLT 2020