# Personalized Federated Learning on Tiny-ImageNet Dirichlet 0.3 (test)

Source: [Personalized Federated Learning on Tiny-ImageNet Dirichlet 0.3 (test)](<https://www.sota2.com/research/sota/personalized-federated-learning-on-tiny-imagenet-dirichlet-0-3-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:26:56.873Z

Evaluation of Personalized Federated Learning performance on the test split of Tiny-ImageNet, using data sampled according to a Dirichlet distribution with alpha=0.3. Metrics include acc@14 and speedup.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Personalized Federated Learning |
| Dataset (including any stated split) | Tiny-ImageNet Dirichlet 0.3 (test) |
| Metric | Acc@14 |
| Unit | SCALAR |
| Direction | Higher is better |
| Results loaded | 0 of 0 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Acc@14](<https://www.sota2.com/research/sota/personalized-federated-learning-on-tiny-imagenet-dirichlet-0-3-test.md?metric=Acc%4014>): Higher is better; unit: SCALAR.

- [Speedup](<https://www.sota2.com/research/sota/personalized-federated-learning-on-tiny-imagenet-dirichlet-0-3-test.md?metric=Speedup>): Higher is better; unit: SCALAR.

## Recorded results

| Method | Acc@14 | Result date | Report paper |
| --- | --- | --- | --- |

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