srs-benchmark
A benchmark for spaced repetition schedulers/algorithms (by open-spaced-repetition)
FedScale
FedScale is a scalable and extensible open-source federated learning (FL) platform. (by SymbioticLab)
srs-benchmark | FedScale | |
---|---|---|
4 | 4 | |
40 | 371 | |
- | 1.3% | |
9.3 | 7.9 | |
about 23 hours ago | 6 months ago | |
Jupyter Notebook | Python | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
srs-benchmark
Posts with mentions or reviews of srs-benchmark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-15.
-
FSRS: A modern, efficient spaced repetition algorithm
I've shared it here in the original ticket that added the benchmark confidence intervals https://github.com/open-spaced-repetition/fsrs-benchmark/iss...
-
FSRS is now the most accurate spaced repetition algorithm in the world*
Here's the link to the benchmark repository: https://github.com/open-spaced-repetition/fsrs-benchmark/tree/Feat/new-dataset
-
In the 1st anniversary of FSRS, I want to share some progress of recent works.
Recently, I have run three comparisons for spaced repetition algorithms. They included SM-15, SM-17, SM-2, HLR, LSTM and FSRS series. The initial result shows that FSRS v4 beats all other algorithms in predicting probability of recall. It's a good news that the open-source algorithm can overperform SuperMemo's proprietary algorithm.
FedScale
Posts with mentions or reviews of FedScale.
We have used some of these posts to build our list of alternatives
and similar projects.
-
University of Michigan Researchers Open-Source ‘FedScale’: a Federated Learning (FL) Benchmarking Suite with Realistic Datasets and a Scalable Runtime to Enable Reproducible FL Research on Privacy-Preserving Machine Learning
Continue reading | Checkout the paper, github link
- We created the most comprehensive benchmark datasets for federated learning to date!
- The most comprehensive benchmark datasets for federated learning to date!
-
The most comprehensive benchmark datasets for federated learning to date
We created FedScale, which has a diverse set of challenging and realistic benchmark datasets to facilitate scalable, comprehensive, and reproducible federated learning (FL) research. FedScale datasets are large-scale, encompassing a diverse range of important FL tasks, such as image classification, object detection, word prediction, and speech recognition. Our evaluation platform provides flexible APIs to implement new FL algorithms and includes new execution backends with minimal developer efforts. Check it out, and feel free to join the FedScale community via Slack(https://join.slack.com/t/fedscale/shared_invite/zt-uzouv5wh-ON8ONCGIzwjXwMYDC2fiKw)!
Paper: https://arxiv.org/abs/2105.11367 and Github repo: https://github.com/symbioticlab/fedscale
Cheers!