On Data-Dependent Random Features for Improved Generalization in Supervised Learning

19 December 2017

Papers citing "On Data-Dependent Random Features for Improved Generalization in Supervised Learning"

7 / 7 papers shown

Title
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
Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks Saurav Prakash S. Dhakal M. Akdeniz Yair Yona S. Talwar Salman Avestimehr N. Himayat FedML 127 93 0 12 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 124 176 0 23 Apr 2020
RFN: A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Spaces Ting-Jui Chang Shahin Shahrampour 47 2 0 12 Feb 2020
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features Liang Ding Rui Tuo Shahin Shahrampour 41 8 0 11 Feb 2020
Self-guided Approximate Linear Programs Parshan Pakiman Selvaprabu Nadarajah Negar Soheili Qihang Lin 16 3 0 09 Jan 2020
ORCCA: Optimal Randomized Canonical Correlation Analysis Yinsong Wang Shahin Shahrampour 94 5 0 11 Oct 2019