spectral approximation

Graph Distillation with Eigenbasis Matching ICML 2024 Error Estimation for Random Fourier Features AISTATS 2023 Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time ICML 2022 A Framework for Private Matrix Analysis in Sliding Window Model ICML 2021 Analysis of stochastic Lanczos quadrature for spectrum approximation ICML 2021 Near-Optimal Entrywise Sampling of Numerically Sparse Matrices COLT 2021 Scaling Neural Tangent Kernels via Sketching and Random Features NeurIPS 2021 Scaling up Kernel Ridge Regression via Locality Sensitive Hashing AISTATS 2020 Streaming Coresets for Symmetric Tensor Factorization ICML 2020 Graph Reduction with Spectral and Cut Guarantees JMLR 2019 On Differentially Private Graph Sparsification and Applications NeurIPS 2019 Spectrally Approximating Large Graphs with Smaller Graphs ICML 2018 Distributed Adaptive Sampling for Kernel Matrix Approximation AISTATS 2017 Multiresolution Kernel Approximation for Gaussian Process Regression NeurIPS 2017 Orthogonal Random Features NeurIPS 2016 Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs ICML 2015