Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees

26 April 2018

Papers citing "Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees"

50 / 95 papers shown

Title
Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Ninh Pham Rasmus Pagh 27 0 0 13 May 2025
Randomized Quasi-Monte Carlo Features for Kernel Approximation Y. Huang Zhen Huang 68 0 0 08 Mar 2025
Kernel Approximation using Analog In-Memory Computing Julian Büchel Giacomo Camposampiero A. Vasilopoulos Corey Lammie Manuel Le Gallo Abbas Rahimi Abu Sebastian 55 0 0 05 Nov 2024
An Online Learning Approach to Prompt-based Selection of Generative Models Xiaoyan Hu Ho-fung Leung Farzan Farnia 38 2 0 17 Oct 2024
Random Features Approximation for Control-Affine Systems Kimia Kazemian Yahya Sattar Sarah Dean 70 1 0 10 Jun 2024
Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport Isaac Reid Stratis Markou Krzysztof Choromanski Richard E. Turner Adrian Weller 27 1 0 26 May 2024
Sketch and shift: a robust decoder for compressive clustering Ayoub Belhadji Rémi Gribonval 19 1 0 15 Dec 2023
A unified framework for learning with nonlinear model classes from arbitrary linear samples Ben Adcock Juan M. Cardenas N. Dexter 31 3 0 25 Nov 2023
Improved Active Learning via Dependent Leverage Score Sampling Atsushi Shimizu Xiaoou Cheng Chris Musco Jonathan Weare FedML 13 5 0 08 Oct 2023
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions Ben Adcock Juan M. Cardenas N. Dexter 24 6 0 01 Jun 2023
On the Size and Approximation Error of Distilled Sets Alaa Maalouf M. Tukan Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 34 4 0 23 May 2023
Quasi-Monte Carlo Graph Random Features Isaac Reid K. Choromanski Adrian Weller 11 8 0 21 May 2023
HPN: Personalized Federated Hyperparameter Optimization Anda Cheng Zhen Wang Yaliang Li Jianwei Cheng 27 1 0 11 Apr 2023
Error Estimation for Random Fourier Features Ju Yao N. Benjamin Erichson Miles E. Lopes 27 6 0 22 Feb 2023
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers K. Choromanski Shanda Li Valerii Likhosherstov Kumar Avinava Dubey Shengjie Luo Di He Yiming Yang Tamás Sarlós Thomas Weingarten Adrian Weller 37 8 0 03 Feb 2023
Efficient Graph Field Integrators Meet Point Clouds K. Choromanski Arijit Sehanobish Han Lin Yunfan Zhao Eli Berger ... Kumar Avinava Dubey Deepali Jain Tamás Sarlós Snigdha Chaturvedi Adrian Weller 15 5 0 02 Feb 2023
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 18 3 0 01 Feb 2023
A Distribution Free Truncated Kernel Ridge Regression Estimator and Related Spectral Analyses Asma Ben Saber Abderrazek Karoui 13 1 0 17 Jan 2023
Localized Contrastive Learning on Graphs Hengrui Zhang Qitian Wu Yu Wang Shaofeng Zhang Junchi Yan Philip S. Yu 22 9 0 08 Dec 2022
RFFNet: Large-Scale Interpretable Kernel Methods via Random Fourier Features Mateus P. Otto Rafael Izbicki 35 1 0 11 Nov 2022
Overparameterized random feature regression with nearly orthogonal data Zhichao Wang Yizhe Zhu 26 3 0 11 Nov 2022
On The Relative Error of Random Fourier Features for Preserving Kernel Distance Kuan Cheng S. Jiang Luojian Wei Zhide Wei 38 1 0 01 Oct 2022
Learning Counterfactually Invariant Predictors Francesco Quinzan Cecilia Casolo Krikamol Muandet Yucen Luo Niki Kilbertus 36 8 0 20 Jul 2022
Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 33 17 0 30 May 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization Simone Bombari Mohammad Hossein Amani Marco Mondelli 25 26 0 20 May 2022
Generalized Reference Kernel for One-class Classification Jenni Raitoharju Alexandros Iosifidis 18 2 0 01 May 2022
Concentration of Random Feature Matrices in High-Dimensions Zhijun Chen Hayden Schaeffer Rachel A. Ward 22 6 0 14 Apr 2022
Near Optimal Reconstruction of Spherical Harmonic Expansions A. Zandieh Insu Han H. Avron 11 0 0 25 Feb 2022
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time David P. Woodruff A. Zandieh 11 9 0 09 Feb 2022
Random Gegenbauer Features for Scalable Kernel Methods Insu Han A. Zandieh H. Avron 21 4 0 07 Feb 2022
Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel Jonas Wacker Ruben Ohana Maurizio Filippone 13 2 0 04 Feb 2022
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning Yuege Xie Bobby Shi Hayden Schaeffer Rachel A. Ward 78 9 0 07 Dec 2021
Bridging the reality gap in quantum devices with physics-aware machine learning D. L. Craig H. Moon F. Fedele D. Lennon B. V. Straaten ... D. Zumbuhl G. Briggs Michael A. Osborne D. Sejdinovic N. Ares 20 13 0 22 Nov 2021
Sharp Analysis of Random Fourier Features in Classification Zhu Li 30 6 0 22 Sep 2021
Learning to Forecast Dynamical Systems from Streaming Data D. Giannakis Amelia Henriksen J. Tropp Rachel A. Ward AI4TS 35 17 0 20 Sep 2021
Deformed semicircle law and concentration of nonlinear random matrices for ultra-wide neural networks Zhichao Wang Yizhe Zhu 35 18 0 20 Sep 2021
Fast Sketching of Polynomial Kernels of Polynomial Degree Zhao-quan Song David P. Woodruff Zheng Yu Lichen Zhang 18 40 0 21 Aug 2021
Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning H. Yamasaki Sho Sonoda 25 6 0 16 Jun 2021
Scaling Neural Tangent Kernels via Sketching and Random Features A. Zandieh Insu Han H. Avron N. Shoham Chaewon Kim Jinwoo Shin 11 31 0 15 Jun 2021
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou A. Gretton MLT 33 35 0 06 Jun 2021
Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features Jinjie Zhang Harish Kannan A. Cloninger Rayan Saab MQ 13 2 0 04 Jun 2021
Nonlinear Matrix Approximation with Radial Basis Function Components E. Rebrova Yu Tang 6 0 0 03 Jun 2021
Random Features for the Neural Tangent Kernel Insu Han H. Avron N. Shoham Chaewon Kim Jinwoo Shin 21 9 0 03 Apr 2021
Learning with Neural Tangent Kernels in Near Input Sparsity Time A. Zandieh 6 0 0 01 Apr 2021
A Temporal Kernel Approach for Deep Learning with Continuous-time Information Da Xu Chuanwei Ruan Evren Körpeoglu Sushant Kumar Kannan Achan SyDa AI4TS 14 4 0 28 Mar 2021
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression Yifan Chen Yun Yang 21 15 0 09 Mar 2021
Quantization Algorithms for Random Fourier Features Xiaoyun Li P. Li MQ 43 13 0 25 Feb 2021
No-Regret Algorithms for Private Gaussian Process Bandit Optimization Abhimanyu Dubey 14 13 0 24 Feb 2021
Learning with Density Matrices and Random Features Fabio A. González Joseph A. Gallego-Mejia Santiago Toledo-Cortés Vladimir Vargas-Calderón 19 29 0 08 Feb 2021
Gauss-Legendre Features for Gaussian Process Regression Paz Fink Shustin H. Avron GP 24 11 0 04 Jan 2021