ACM MMSys 2024 Bandwidth Estimation in Real Time Communications Challenge

Author:

Khairy Sami1ORCID,Mittag Gabriel1ORCID,Gopal Vishak1ORCID,Yan Francis Y.2ORCID,Niu Zhixiong2ORCID,Ameri Ezra1ORCID,Inglis Scott1ORCID,Golestaneh Mehrsa1ORCID,Cutler Ross1ORCID

Affiliation:

1. Microsoft

2. Microsoft Research

Publisher

ACM

Reference29 articles.

1. Abdelhak Bentaleb, Mehmet N Akcay, May Lim, Ali C Begen, and Roger Zimmermann. 2022. BoB: Bandwidth prediction for real-time communications using heuristic and reinforcement learning. IEEE Transactions on Multimedia (2022).

2. Ekrem Cetinkaya, Ahmet Pehlivanoglu, Ihsan U. Ayten, Basar Yumakogullari, Mehmet E. Ozgun, Yigit K. Erinc, Enes Deniz, and Ali C. Begen. 2024. Offline Reinforcement Learning for Bandwidth Estimation in RTC Using a Fast Actor and not-So-Furious Critic. In Proceedings of the 15th ACM Multimedia Systems Conference.

3. OpenNetLab: Open Platform for RL-based Congestion Control for Real-Time Communications

4. A closer look at offline rl agents;Fu Yuwei;Advances in Neural Information Processing Systems,2022

5. Scott Fujimoto and Shixiang Shane Gu. 2021. A minimalist approach to offline reinforcement learning. Advances in neural information processing systems 34 (2021), 20132--20145.

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