kernel methods

Learning with invariances in random features and kernel models COLT 2021 Maximum Mean Discrepancy Test is Aware of Adversarial Attacks ICML 2021 Meta Learning on a Sequence of Imbalanced Domains With Difficulty Awareness ICCV 2021 Meta-Learning with Neural Tangent Kernels ICLR 2021 Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data NeurIPS 2021 Misspecified Gaussian Process Bandit Optimization NeurIPS 2021 Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021 Neural Splines: Fitting 3D Surfaces With Infinitely-Wide Neural Networks CVPR 2021 Neural Tangent Kernel Maximum Mean Discrepancy NeurIPS 2021 Nonlinear Functional Output Regression: A Dictionary Approach AISTATS 2021 Nonparametric estimation of continuous DPPs with kernel methods NeurIPS 2021 No-regret Algorithms for Capturing Events in Poisson Point Processes ICML 2021 Oblivious Data for Fairness with Kernels JMLR 2021 On Information Gain and Regret Bounds in Gaussian Process Bandits AISTATS 2021 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization ICML 2021 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game ICML 2021 On the Sample Complexity of Learning under Geometric Stability NeurIPS 2021 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search ICML 2021 Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning NeurIPS 2021 Partial Multi-Label Optimal Margin Distribution Machine IJCAI 2021 Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers NeurIPS 2021 Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction ICML 2021 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels ICML 2021 Refined Learning Bounds for Kernel and Approximate k-Means NeurIPS 2021 Regret Bounds for Online Kernel Selection in Continuous Kernel Space AAAI 2021