conftrace_

reproducing kernel hilbert space

334 papers

Explore in graph

Also known as

RKHS

Co-occurring keywords

kernel methods (1097) gaussian process (1200) maximum mean discrepancy (164) regret bound (1926) kernel ridge regression (111) support vector machine (978) convex optimization (1321) kernel mean embedding (43) generalization bound (652) bayesian optimization (624)

Papers

Learning-Based Image Registration With Meta-Regularization CVPR 2021
Misspecified Gaussian Process Bandit Optimization NIPS 2021
Deconditional Downscaling with Gaussian Processes NIPS 2021
Gradient Descent in RKHS with Importance Labeling AISTATS 2021
Improved Mutual Information Estimation AAAI 2021
Pure Exploration in Kernel and Neural Bandits NIPS 2021
Counterfactual Mean Embeddings JMLR 2021
Framing RNN as a kernel method: A neural ODE approach NIPS 2021
Application of kernel hypothesis testing on set-valued data UAI 2021
Generalization Properties of hyper-RKHS and its Applications JMLR 2021
No-regret Algorithms for Capturing Events in Poisson Point Processes ICML 2021
On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization ICML 2021
Last iterate convergence of SGD for Least-Squares in the Interpolation regime. NIPS 2021
Generative Particle Variational Inference via Estimation of Functional Gradients ICML 2021
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings AISTATS 2021
Nonparametric Continuous Sensor Registration JMLR 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NIPS 2021
An analysis of Ermakov-Zolotukhin quadrature using kernels NIPS 2021
On the Similarity between the Laplace and Neural Tangent Kernels NIPS 2020
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization AISTATS 2020
Kernel Conditional Moment Test via Maximum Moment Restriction UAI 2020
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms JMLR 2020
Learning Fair Representations for Kernel Models AISTATS 2020
HoMM: Higher-Order Moment Matching for Unsupervised Domain Adaptation AAAI 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020