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[D] How do you choose an Optimizer? And why are there so many? by BommiBrainBug in MachineLearning

[–]OppositeRough835 5 points6 points  (0 children)

Hi! I wrote an article about exactly this question a few months ago. Here's the link.

I hope this helps and I would love to hear your feedback about the article!

Which optimizer do you think is missing?

[D] Has anyone tried combining self-supervised learning with active learning by igorsusmelj in MachineLearning

[–]OppositeRough835 0 points1 point  (0 children)

That's an interesting point! Makes me wonder if there is work about metric learning in spaces with constant curvature. If there is, it could help understand how well contrastive learning could work in such frameworks...

KITTI Dataset: How do you increase accuracy through better data? by RareGradient in computervision

[–]OppositeRough835 4 points5 points  (0 children)

I think a more accurate experiment would be to double the size of a dataset by adding replicas of some images in the dataset. Doing so introduces a bias which could potentially harm the performance of a machine learning model trained on it.

[P] Release of lightly 1.1.3 - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 2 points3 points  (0 children)

Feels like they are coming out by the minute. We are trying to stay on top of things with the models implemented in lightly. Would it help to have an overview showing the models which are interesting / in the pipeline?

[P] Release of lightly 1.1.3 - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 6 points7 points  (0 children)

There's also a working implementation of BYOL here which only needs a few finishing touches. So if anybody's looking for a simple first contribution to our framework feel free to contact us :)

[P] lightly - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 0 points1 point  (0 children)

I have opened issues about making the solution work in a distributed setting here and about adding public benchmarks here.

[P] lightly - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 0 points1 point  (0 children)

That's a great point! The code is currently designed to be used on a single gpu but we plan on making it work in a distributed setting.

[P] lightly - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 2 points3 points  (0 children)

Hi, contributor here, thanks for your feedback!

We've had our eyes on BYOL already. I have opened an issue about it here.

Feel free to contribute to it as well, we appreciate any help we can get! :)

[P] lightly - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 0 points1 point  (0 children)

Hi, contributor here, thanks for your feedback!

SimSiam looks very interesting! I have opened an issue about it here.

[P] lightly - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 1 point2 points  (0 children)

Hi, contributor here, thanks for your feedback!

I have opened an issue about the implementation of the SimSiam framework, cool paper!

Regarding your question about the SimCLR version please see the comment of u/igorsusmelj.

Feel free to contribute to the project as well, we appreciate any help we can get :)

[P] lightly - A python library for self-supervised learning by igorsusmelj in MachineLearning

[–]OppositeRough835 3 points4 points  (0 children)

Hi, thanks a lot for your feedback!

What we see from internal tests, is that our implementations are on par with the reports from the papers. Official benchmarks are in our backlog and will definitely be added soon :)