kernel matrix

Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering ICML 2021 A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent NeurIPS 2020 Extractive Financial Narrative Summarisation based on DPPs COLING 2020 Fast geometric learning with symbolic matrices NeurIPS 2020 Learning Data-adaptive Non-parametric Kernels JMLR 2020 Linear Time Sinkhorn Divergences using Positive Features NeurIPS 2020 On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis AISTATS 2020 On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels COLT 2020 Sampling from a k-DPP without looking at all items NeurIPS 2020 Approximate Kernel Selection with Strong Approximate Consistency AAAI 2019 Exact Gaussian Processes on a Million Data Points NeurIPS 2019 Learning Nonsymmetric Determinantal Point Processes NeurIPS 2019 Similarity Learning via Kernel Preserving Embedding AAAI 2019 Exploiting Graph Regularized Multi-dimensional Hawkes Processes for Modeling Events with Spatio-temporal Characteristics IJCAI 2018 GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration NeurIPS 2018 Efficient Kernel Selection via Spectral Analysis IJCAI 2017 Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? NeurIPS 2017 Memory Efficient Kernel Approximation JMLR 2017 Nyström Method with Kernel K-means++ Samples as Landmarks ICML 2017 Recursive Sampling for the Nystrom Method NeurIPS 2017 Translation Synchronization via Truncated Least Squares NeurIPS 2017 Gromov-Wasserstein Averaging of Kernel and Distance Matrices ICML 2016 Preconditioning Kernel Matrices ICML 2016 Revisiting the Nyström Method for Improved Large-scale Machine Learning JMLR 2016 Beyond Covariance: Feature Representation With Nonlinear Kernel Matrices ICCV 2015