Data-driven Random Fourier Features using Stein Effect

Data-driven Random Fourier Features using Stein Effect

23 May 2017

Wei-Cheng Chang

Chun-Liang Li

Barnabás Póczós

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Papers citing "Data-driven Random Fourier Features using Stein Effect"

9 / 9 papers shown

Title
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney UQCV 65 6 0 14 Oct 2022
On The Relative Error of Random Fourier Features for Preserving Kernel Distance Kuan Cheng S. Jiang Luojian Wei Zhide Wei 90 1 0 01 Oct 2022
Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning H. Yamasaki Sho Sonoda 63 6 0 16 Jun 2021
Learning to Learn Kernels with Variational Random Features Xiantong Zhen Hao Sun Yingjun Du Jun Xu Yilong Yin Ling Shao Cees G. M. Snoek DRL 72 34 0 11 Jun 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 124 176 0 23 Apr 2020
ORCCA: Optimal Randomized Canonical Correlation Analysis Yinsong Wang Shahin Shahrampour 94 5 0 11 Oct 2019
Data-dependent compression of random features for large-scale kernel approximation Raj Agrawal Trevor Campbell Jonathan H. Huggins Tamara Broderick 48 20 0 09 Oct 2018
On Data-Dependent Random Features for Improved Generalization in Supervised Learning Shahin Shahrampour Ahmad Beirami Vahid Tarokh 34 27 0 19 Dec 2017
Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features Jean-François Ton Seth Flaxman Dino Sejdinovic Samir Bhatt GP 73 55 0 15 Nov 2017

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