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Random Features for Kernel Approximation: A Survey on Algorithms,
  Theory, and Beyond

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond

23 April 2020
Fanghui Liu
Xiaolin Huang
Yudong Chen
Johan A. K. Suykens
    BDL
ArXivPDFHTML

Papers citing "Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond"

24 / 24 papers shown
Title
Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation
Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation
Ninh Pham
Rasmus Pagh
27
0
0
13 May 2025
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model
Jinchao Feng
Sui Tang
26
0
0
11 May 2025
Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model
Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model
Sasan Vakili
Manuel Mazo Jr.
Peyman Mohajerin Esfahani
28
0
0
07 Apr 2025
Training Hybrid Neural Networks with Multimode Optical Nonlinearities Using Digital Twins
Training Hybrid Neural Networks with Multimode Optical Nonlinearities Using Digital Twins
Ilker Oguz
Louis J. E. Suter
J. Hsieh
Mustafa Yildirim
Niyazi Ulaş Dinç
Christophe Moser
D. Psaltis
58
2
0
14 Jan 2025
Optimal Kernel Quantile Learning with Random Features
Optimal Kernel Quantile Learning with Random Features
Caixing Wang
Xingdong Feng
42
0
0
24 Aug 2024
On the choice of the non-trainable internal weights in random feature maps
On the choice of the non-trainable internal weights in random feature maps
Pinak Mandal
Georg Gottwald
Nicholas Cranch
TPM
40
1
0
07 Aug 2024
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features
Oliver R. A. Dunbar
Nicholas H. Nelsen
Maya Mutic
30
5
0
30 Jun 2024
Boosting Nyström Method
Boosting Nyström Method
Keaton Hamm
Zhaoying Lu
Wenbo Ouyang
Hao Helen Zhang
21
0
0
21 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models
Precise Asymptotic Analysis of Deep Random Feature Models
David Bosch
Ashkan Panahi
B. Hassibi
35
19
0
13 Feb 2023
LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection
LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection
Joseph A. Gallego-Mejia
Oscar A. Bustos-Brinez
Fabio A. González
44
2
0
15 Nov 2022
Provably Reliable Large-Scale Sampling from Gaussian Processes
Provably Reliable Large-Scale Sampling from Gaussian Processes
Anthony Stephenson
Robert Allison
Edward O. Pyzer-Knapp
21
2
0
15 Nov 2022
Gradient-enhanced deep neural network approximations
Gradient-enhanced deep neural network approximations
Xiaodong Feng
Li Zeng
UQCV
26
5
0
08 Nov 2022
LARF: Two-level Attention-based Random Forests with a Mixture of
  Contamination Models
LARF: Two-level Attention-based Random Forests with a Mixture of Contamination Models
A. Konstantinov
Lev V. Utkin
36
0
0
11 Oct 2022
Improved Anomaly Detection by Using the Attention-Based Isolation Forest
Improved Anomaly Detection by Using the Attention-Based Isolation Forest
Lev V. Utkin
A. Ageev
A. Konstantinov
41
6
0
05 Oct 2022
On The Relative Error of Random Fourier Features for Preserving Kernel
  Distance
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
Random Fourier Features for Asymmetric Kernels
Random Fourier Features for Asymmetric Kernels
Ming-qian He
Fan He
Fanghui Liu
Xiaolin Huang
22
3
0
18 Sep 2022
Generalized Leverage Scores: Geometric Interpretation and Applications
Generalized Leverage Scores: Geometric Interpretation and Applications
Bruno Ordozgoiti
Antonis Matakos
Aristides Gionis
32
4
0
16 Jun 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via
  Distance-Awareness
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
J. Liu
Shreyas Padhy
Jie Jessie Ren
Zi Lin
Yeming Wen
Ghassen Jerfel
Zachary Nado
Jasper Snoek
Dustin Tran
Balaji Lakshminarayanan
UQCV
BDL
21
48
0
01 May 2022
Concentration of Random Feature Matrices in High-Dimensions
Concentration of Random Feature Matrices in High-Dimensions
Zhijun Chen
Hayden Schaeffer
Rachel A. Ward
22
6
0
14 Apr 2022
Local Random Feature Approximations of the Gaussian Kernel
Local Random Feature Approximations of the Gaussian Kernel
Jonas Wacker
Maurizio Filippone
22
3
0
12 Apr 2022
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy
  Regime
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime
Stéphane dÁscoli
Maria Refinetti
Giulio Biroli
Florent Krzakala
93
152
0
02 Mar 2020
Gaussian Processes with Errors in Variables: Theory and Computation
Gaussian Processes with Errors in Variables: Theory and Computation
Shuang Zhou
D. Pati
Tianying Wang
Yun Yang
R. Carroll
16
3
0
14 Oct 2019
Structured adaptive and random spinners for fast machine learning
  computations
Structured adaptive and random spinners for fast machine learning computations
Mariusz Bojarski
A. Choromańska
K. Choromanski
Francois Fagan
Cédric Gouy-Pailler
Anne Morvan
Nourhan Sakr
Tamás Sarlós
Jamal Atif
35
35
0
19 Oct 2016
Sharp analysis of low-rank kernel matrix approximations
Sharp analysis of low-rank kernel matrix approximations
Francis R. Bach
86
277
0
09 Aug 2012
1