kernel matrix

Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees UAI 2025 Towards an Explainable Comparison and Alignment of Feature Embeddings ICML 2025 Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic ICML 2024 Entrywise error bounds for low-rank approximations of kernel matrices NeurIPS 2024 Fast Dynamic Sampling for Determinantal Point Processes AISTATS 2024 Large-Scale Gaussian Processes via Alternating Projection AISTATS 2024 Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation ICML 2024 Improved Kernel Alignment Regret Bound for Online Kernel Learning AAAI 2023 Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition JMLR 2023 Randomized Primal-Dual Methods with Adaptive Step Sizes AISTATS 2023 Robust and Fast Measure of Information via Low-Rank Representation AAAI 2023 Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation ICLR 2023 A Perturbation-Based Kernel Approximation Framework JMLR 2022 A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources ICML 2022 Giga-scale Kernel Matrix-Vector Multiplication on GPU NeurIPS 2022 Kernel similarity matching with Hebbian networks NeurIPS 2022 Preconditioning for Scalable Gaussian Process Hyperparameter Optimization ICML 2022 Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes ICML 2022 Scalable Sampling for Nonsymmetric Determinantal Point Processes ICLR 2022 The Fast Kernel Transform AISTATS 2022 A Deep Conditioning Treatment of Neural Networks ALT 2021 Faster Kernel Matrix Algebra via Density Estimation ICML 2021 Fast Statistical Leverage Score Approximation in Kernel Ridge Regression AISTATS 2021 High-Dimensional Gaussian Process Inference with Derivatives ICML 2021 Kernel Operations on the GPU, with Autodiff, without Memory Overflows JMLR 2021