Grand challenge at ACM MMSys 2024

2nd Bandwidth Estimation Grand Challenge at ACM MMSys 2024

Dear colleagues,

We are excited to announce that we are hosting the 2nd bandwidth estimation grand challenge at ACM MMSys 2024, Bari, Italy. The challenge is focused on the development of a deep learning-based bandwidth estimator for real time video communications using offline reinforcement learning (RL). Details can be found at:

1. Challenge website: https://www.microsoft.com/en-us/research/academic-program/bandwidth-estimation-challenge/

2. GitHub repository: https://github.com/microsoft/RL4BandwidthEstimationChallenge/

3. ACM MMSys 2024 website: https://2024.acmmmsys.org/

The challenge is open to researchers and practitioners from academia and industry, and we welcome submissions from teams or individuals. The deadline for submitting the bandwidth estimation model, code, and paper to the Open-source Software and Datasets Track is on January 5th, 2024. Accepted papers will be included in the ACM MMSys 2024 conference proceedings, and code submissions will be given the appropriate ACM reproducibility badge. Moreover, the winner and the runner-up will be awarded cash prizes.

We hope that you will join us in this exciting challenge and contribute to the advancing of bandwidth estimation for real time video communications. If you have any questions or feedback, please feel free to contact us.

Best regards,

The bandwidth estimation challenge organizers

Sami Khairy, Gabriel Mittag, Ezra Ameri, Scott Inglis, Vishak Gopal, Mehrsa Golestaneh, Ross Cutler (Microsoft Corporation)
Francis Yan, Zhixiong Niu (Microsoft Research)

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