nystrom method

MoDeGPT: Modular Decomposition for Large Language Model Compression ICLR 2025 On the Approximation of Kernel functions JMLR 2025 Correspondence-Free Non-Rigid Point Set Registration Using Unsupervised Clustering Analysis CVPR 2024 Differential Privacy in Scalable General Kernel Learning via K-means Nystr\"om Random Features NeurIPS 2024 Nyström Method for Accurate and Scalable Implicit Differentiation AISTATS 2023 Communication Efficient Distributed Learning for Kernelized Contextual Bandits NeurIPS 2022 Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022 Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA JMLR 2022 Sublinear Time Approximation of Text Similarity Matrices AAAI 2022 Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract) IJCAI 2021 Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention AAAI 2021 Refined Learning Bounds for Kernel and Approximate k-Means NeurIPS 2021 Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method NeurIPS 2021 Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method NeurIPS 2020 Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis IJCAI 2019 Efficient online learning with kernels for adversarial large scale problems NeurIPS 2019 Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses NeurIPS 2019 Scalable Learning in Reproducing Kernel Krein Spaces ICML 2019 Fast Cross-Validation IJCAI 2018 Multi-scale Nystrom Method AISTATS 2018 Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF) ICML 2018 Statistical and Computational Trade-Offs in Kernel K-Means NeurIPS 2018 Hierarchically Compositional Kernels for Scalable Nonparametric Learning JMLR 2017 Recursive Sampling for the Nystrom Method NeurIPS 2017 Storage Fit Learning with Unlabeled Data IJCAI 2017