Research map / Learning theory and algorithms / Kernels and regression theory
On the Optimality of Misspecified Kernel Ridge Regression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace the boundedness assumption on the true function with an Lq-integrability assumption | KRR for general RKHS · s + 1/β > α₀ | L2 excess-risk convergence rate: n^{-\frac{s \beta}{s \beta +1}} | Helped |
| Apply KRR to a Sobolev RKHS without assuming the target function is bounded | KRR · Sobolev RKHS, 0 < s ≤ 2 | L2 excess-risk convergence rate: n^{-\frac{s \beta}{s \beta +1}} | Helped |
| Use KRR with the unbounded target function and λ = c n^{-\frac{10}{9}} | KRR · Sobolev RKHS, s=0.4 | generalization-error convergence rate: n^{-\frac{4}{9}} | Helped |
| Use KRR with the unbounded target function | KRR · General RKHS, s=0.4 | generalization-error convergence rate: n^{-\frac{4}{9}} | Helped |
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