conftrace_

reproducing kernel hilbert space

334 papers

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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

Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach ICML 2023
Adaptive Learning of Density Ratios in RKHS JMLR 2023
A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points JMLR 2023
Compressed Decentralized Learning of Conditional Mean Embedding Operators in Reproducing Kernel Hilbert Spaces AAAI 2023
On the Optimality of Misspecified Kernel Ridge Regression ICML 2023
Metrizing Weak Convergence with Maximum Mean Discrepancies JMLR 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
Statistical Robustness of Empirical Risks in Machine Learning JMLR 2023
Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model NIPS 2023
On kernel-based statistical learning theory in the mean field limit NIPS 2023
Kernel Quadrature with Randomly Pivoted Cholesky NIPS 2023
Interpolating Classifiers Make Few Mistakes JMLR 2023
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws AISTATS 2023
Practical Markov Boundary Learning without Strong Assumptions AAAI 2023
Active Cost-aware Labeling of Streaming Data AISTATS 2023
Multi-Layer Neural Networks as Trainable Ladders of Hilbert Spaces ICML 2023
Functional Renyi Differential Privacy for Generative Modeling NIPS 2023
On Distance and Kernel Measures of Conditional Dependence JMLR 2023
On the geometry of Stein variational gradient descent JMLR 2023
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces JMLR 2023
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift NIPS 2023
Deep learning with kernels through RKHM and the Perron-Frobenius operator NIPS 2023
Nonparametric adaptive control and prediction: theory and randomized algorithms JMLR 2022
Learning Inconsistent Preferences with Gaussian Processes AISTATS 2022
Open Problem: Regret Bounds for Noise-Free Kernel-Based Bandits COLT 2022