atlas

Research map / Learning theory and algorithms / Kernels and regression theory

Recycling Randomness with Structure for Sublinear time Kernel Expansions

ICML 2016 · Learning theory and algorithms › Kernels and regression theory · approach: RKHS kernel methods · 30 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use Toeplitz-like semi-Gaussian features with displacement rank 20 instead of Gaussian random featuresKernel random feature maps · USPS (k=256), kernel approximation errorkernel approximation error (%): 5.06 -> 6.68Hurt
Use Toeplitz-like semi-Gaussian features with displacement rank 20 instead of Gaussian random featuresKernel random feature maps · USPS (k=256), classificationclassification error (%): 7.12 -> 7.29Hurt
Use Toeplitz-like semi-Gaussian features with displacement rank 20 instead of Gaussian random featuresKernel random feature maps · DNA (k=80), classificationclassification error (%): 31.04 -> 30.70Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · USPS (k=256)kernel approximation error (%): 9.66 -> 6.68Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · USPS (k=1280)kernel approximation error (%): 4.41 -> 3.00Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · DNA (k=80)kernel approximation error (%): 6.26 -> 4.10Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · DNA (k=900)kernel approximation error (%): 2.88 -> 1.83Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · COIL (k=1024)kernel approximation error (%): 5.60 -> 3.79Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · COIL (k=2048)kernel approximation error (%): 4.18 -> 2.76Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · USPS (k=1280)classification error (%): 4.62 -> 4.65No clear effect
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · DNA (k=80)classification error (%): 31.35 -> 30.70Helped
Increase Toeplitz-like displacement rank from 1 to 20 (ablation)Toeplitz-like kernel features · COIL (k=1024)classification error (%): 0.62 -> 0.52Hurt

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy