v1v2v3v4 (latest)

Quadrature-based features for kernel approximation

11 February 2018

Papers citing "Quadrature-based features for kernel approximation"

20 / 20 papers shown

Title
Feature maps for the Laplacian kernel and its generalizations Sudhendu Ahir Parthe Pandit 99 0 0 24 Feb 2025
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 109 5 0 02 Oct 2024
Spectraformer: A Unified Random Feature Framework for Transformer Duke Nguyen Du Yin Aditya Joshi Flora D. Salim 69 1 0 24 May 2024
Robust representations of oil wells' intervals via sparse attention mechanism Alina Rogulina N. Baramiia Valerii Kornilov Sergey Petrakov Alexey Zaytsev AI4TS OOD 69 1 0 29 Dec 2022
Arithmetic Circuits, Structured Matrices and (not so) Deep Learning Atri Rudra 54 1 0 24 Jun 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 134 19 0 30 Apr 2022
Monarch: Expressive Structured Matrices for Efficient and Accurate Training Tri Dao Beidi Chen N. Sohoni Arjun D Desai Michael Poli Jessica Grogan Alexander Liu Aniruddh Rao Atri Rudra Christopher Ré 141 97 0 01 Apr 2022
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models Tri Dao Beidi Chen Kaizhao Liang Jiaming Yang Zhao Song Atri Rudra Christopher Ré 133 79 0 30 Nov 2021
Efficient Fourier representations of families of Gaussian processes P. Greengard 86 3 0 28 Sep 2021
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels Qin Luo Kun Fang Jie Yang Xiaolin Huang 40 1 0 13 Apr 2021
No-Regret Algorithms for Private Gaussian Process Bandit Optimization Abhimanyu Dubey 66 13 0 24 Feb 2021
Gauss-Legendre Features for Gaussian Process Regression Paz Fink Shustin H. Avron GP 59 11 0 04 Jan 2021
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps Tri Dao N. Sohoni Albert Gu Matthew Eichhorn Amit Blonder Megan Leszczynski Atri Rudra Christopher Ré 90 49 0 29 Dec 2020
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens 88 4 0 03 Nov 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 126 176 0 23 Apr 2020
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features Liang Ding Rui Tuo Shahin Shahrampour 41 8 0 11 Feb 2020
Tensor Completion via Gaussian Process Based Initialization Yermek Kapushev Ivan Oseledets Evgeny Burnaev 60 6 0 11 Dec 2019
Butterfly Transform: An Efficient FFT Based Neural Architecture Design Keivan Alizadeh-Vahid Anish K. Prabhu Ali Farhadi Mohammad Rastegari 138 50 0 05 Jun 2019
Kernel Mean Embedding Based Hypothesis Tests for Comparing Spatial Point Patterns Raif M. Rustamov James T. Klosowski 58 7 0 31 May 2019
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations Tri Dao Albert Gu Matthew Eichhorn Atri Rudra Christopher Ré 144 108 0 14 Mar 2019