Pages that link to "Item:Q5361284"

The following pages link to On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions (Q5361284):

Displaying 40 items.

• The Hardness of Conditional Independence Testing and the Generalised Covariance Measure (Q118262) (← links)
• Generalization properties of doubly stochastic learning algorithms (Q1635837) (← links)
• Linearized two-layers neural networks in high dimension (Q2039801) (← links)
• Fast generalization error bound of deep learning without scale invariance of activation functions (Q2055056) (← links)
• Supervised learning from noisy observations: combining machine-learning techniques with data assimilation (Q2077682) (← links)
• Convolutional spectral kernel learning with generalization guarantees (Q2093403) (← links)
• Generalization error of random feature and kernel methods: hypercontractivity and kernel matrix concentration (Q2134105) (← links)
• Data-independent random projections from the feature-map of the homogeneous polynomial kernel of degree two (Q2195436) (← links)
• Convergence analysis of deterministic kernel-based quadrature rules in misspecified settings (Q2291733) (← links)
• Symmetry exploits for Bayesian cubature methods (Q2302452) (← links)
• Compressive statistical learning with random feature moments (Q2664824) (← links)
• Bayesian Approximate Kernel Regression With Variable Selection (Q3121562) (← links)
• The Random Feature Model for Input-Output Maps between Banach Spaces (Q3382802) (← links)
• Optimal Quadrature-Sparsification for Integral Operator Approximation (Q4553791) (← links)
• On b-bit min-wise hashing for large-scale regression and classification with sparse data (Q4558503) (← links)
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• A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent* (Q5020045) (← links)
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• Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions (Q5119635) (← links)
• Spurious Valleys in Two-layer Neural Network Optimization Landscapes (Q5214225) (← links)
• Randomized numerical linear algebra: Foundations and algorithms (Q5887823) (← links)
• HARFE: hard-ridge random feature expansion (Q6049834) (← links)
• Transferable neural networks for partial differential equations (Q6123346) (← links)
• Learning to Forecast Dynamical Systems from Streaming Data (Q6168204) (← links)
• Benign Overfitting and Noisy Features (Q6185582) (← links)
• Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition (Q6202283) (← links)
• Kernel embedding of measures and low-rank approximation of integral operators (Q6500136) (← links)
• Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations (Q6557699) (← links)
• SRMD: sparse random mode decomposition (Q6575285) (← links)
• Operator learning using random features: a tool for scientific computing (Q6585281) (← links)
• Deformed semicircle law and concentration of nonlinear random matrices for ultra-wide neural networks (Q6590448) (← links)
• Fast kernel summation in high dimensions via slicing and Fourier transforms (Q6655077) (← links)
• Finding global minima via kernel approximations (Q6665395) (← links)