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Random Gegenbauer Features for Scalable Kernel Methods.

, , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 8330-8358. PMLR, (2022)

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Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling., and . ICML, volume 119 of Proceedings of Machine Learning Research, page 10324-10333. PMLR, (2020)Efficiently Learning Fourier Sparse Set Functions., , , and . NeurIPS, page 15094-15103. (2019)Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time., and . ICML, volume 162 of Proceedings of Machine Learning Research, page 23933-23964. PMLR, (2022)HyperAttention: Long-context Attention in Near-Linear Time., , , , , and . ICLR, OpenReview.net, (2024)HyperAttention: Long-context Attention in Near-Linear Time., , , , , and . CoRR, (2023)Scaling Neural Tangent Kernels via Sketching and Random Features., , , , , and . NeurIPS, page 1062-1073. (2021)KDEformer: Accelerating Transformers via Kernel Density Estimation., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 40605-40623. PMLR, (2023)Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms., , , , , and . SODA, page 4768-4845. SIAM, (2023)Oblivious Sketching of High-Degree Polynomial Kernels., , , , , , and . SODA, page 141-160. SIAM, (2020)Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees., , , , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 253-262. PMLR, (2017)