Research map / Learning theory and algorithms / Sample complexity
Distributed Nonparametric Regression under Communication Constraints
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase total communication so that it remains below the effective dimension for local sample size | Distributed nonparametric estimation · Sobolev function class, insufficient communication regime | minimax squared ℓ2 risk: (mb)^{-2\alpha} | Helped |
| Allocate communication to estimate each coefficient from multiple machines | Distributed nonparametric estimation · Sobolev function class, intermediate communication regime | minimax squared ℓ2 risk: (mnb)^{-\frac{\alpha}{\alpha+1}} | Helped |
| Increase each machine's communication budget beyond the effective dimension at global noise level | Distributed nonparametric estimation · Sobolev function class, sufficient communication regime | minimax squared ℓ2 risk: (mn)^{-\frac{2\alpha}{2\alpha+1}} | Helped |
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