Double Descent Curve with Optical Random Features
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Updated
Jun 22, 2022 - Jupyter Notebook
Double Descent Curve with Optical Random Features
Quadrature-based features for kernel approximation
A library for random feature maps in Python.
Multi-Shot Approximation of Discounted Cost MDPs
Enitor provides the MATLAB implementation of several large-scale kernel methods.
Fast Random Kernelized Features: Support Vector Machine Classification for High-Dimensional IDC Dataset
A Random Matrix Approach for Random Feature Maps
Codes and experiments for paper "Automated Spectral Kernel Learning". Preprint.
Codes and experiments for paper "Distributed Learning with Random Features". Preprint.
Reference implementation for our paper "Curiously Effective Features for Image Quality Prediction"
Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
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