Easeml name dispute

This is a request to be assigned the name “easeml” for our snap, instead of “easeml-automl”, we filed a dispute already in February 2020 but we are still waiting for the resolution.

Snap ID: wDn2qvfuqRxhWCnCcypmwSBIcc5uA8wa

Summary: Ease.ml is a declarative machine learning service platform.

Publisher

Display name: Easeml

Store username: easeml

Account ID: j5UFRP90YqesLyacPYeWxwm7bSIqiIIa

Case:

The name easeml seems to be taken already in the snap store without any snap using it. We have an already working snap and a strong claim to the name with several years of work using that name:

The website:

http://ease.ml/

7 academic articles using the name:

Zhang, Ce, Wentao Wu, and Tian Li. “An overreaction to the broken machine learning abstraction: The ease. ml vision.” Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics. 2017.

Karlaš, B., Liu, J., Wu, W., & Zhang, C. (2018). Ease. ml in action: towards multi-tenant declarative learning services. Proceedings of the VLDB Endowment, 11(12), 2054-2057.

Li, T., Zhong, J., Liu, J., Wu, W., & Zhang, C. (2018). Ease. ml: Towards multi-tenant resource sharing for machine learning workloads. Proceedings of the VLDB Endowment, 11(5), 607-620.

Renggli, C., Hubis, F. A., Karlaš, B., Schawinski, K., Wu, W., & Zhang, C. (2019). Ease. ml/ci and Ease. ml/meter in action: towards data management for statistical generalization. Proceedings of the VLDB Endowment, 12(12), 1962-1965.

Renggli, C., Karlaš, B., Ding, B., Liu, F., Schawinski, K., Wu, W., & Zhang, C. (2019). Continuous integration of machine learning models with ease. ml/ci: Towards a rigorous yet practical treatment. arXiv preprint arXiv:1903.00278.

Hubis, F. A., Wu, W., & Zhang, C. (2019). Ease. ml/meter: Quantitative overfitting management for human-in-the-loop ml application development. arXiv preprint arXiv:1906.00299.

Renggli, C., Hubis, F. A., Karlaš, B., Schawinski, K., Wu, W., & Zhang, C. (2019). Ease. ml/ci and Ease. ml/meter in action: towards data management for statistical generalization. Proceedings of the VLDB Endowment, 12(12), 1962-1965.

Kind Regards,
Leonel Aguilar
Data Science Service and Systems Group
ETH Zurich

I wonder if yo maybe didn’t click the final “submit” button - I just checked my board and didn’t find any disputes for easeml.

Please go ahead and file a new one and we’ll have a look.

  • Daniel
1 Like

@roadmr, thanks for your input! Please let us know if something else is needed.

@roadmr, the problem has been fixed.

Thanks for your prompt help!

Kind regards,
Leonel

1 Like

I’m really happy the store team managed to get you access to your preferred name. As an aside, while acknowledging that I know very little of ML, your project looks awesome! :slight_smile:

1 Like