Nyström Approximation
Cross-source consensus on Nyström Approximation from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Preparation
Evidence quality
Highlighted claims
- Projected attraction can use cached training-set summaries for the numerator and denominator. — DriftXpress: Faster Drifting Models via Projected RKHS Fields
- DriftXpress selects fixed landmarks from training samples before training, usually by random per-class sampling. — DriftXpress: Faster Drifting Models via Projected RKHS Fields
- Field approximation fidelity improves as the number of landmarks per class increases. — DriftXpress: Faster Drifting Models via Projected RKHS Fields
- The projected kernel is computed as an inner product of Nyström features. — DriftXpress: Faster Drifting Models via Projected RKHS Fields