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- Puffer
Puffer is a research project in the computer science department at Stanford University Please find more details in the FAQ and our research paper (USENIX NSDI '20 Community Award, IRTF Applied Networking Research Prize '21)
- Puffer - Stanford University
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- Puffer - Stanford University
Puffer is a Stanford University research study about using machine learning to improve video-streaming algorithms: the kind of algorithms used by services such as YouTube, Netflix, and Twitch We are trying to figure out how to teach a computer to design new algorithms that reduce glitches and stalls in streaming video (especially over wireless networks and those with limited capacity, such as
- Puffer - Stanford University
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- Puffer - Stanford University
The plots show 95% confidence intervals Confidence intervals are particularly important in Puffer: As discussed in the research paper, we find that the variable and heavy-tailed nature of video streaming requires remarkably large amounts of data in order to draw statistically significant conclusions about a scheme’s performance
- Puffer - Stanford University
Selected date (UTC): 2026-03-22T11_2026-03-23T11 (share a permalink) Full results: Storage bucket Retrained model: 20260322-1 tar gz video_sent measurement: video
- Learning in situ: a randomized experiment in video streaming
Puffer receives six television channels using a VHF UHF antenna and an ATSC demodulator, which outputs MPEG-2 transport streams in UDP We wrote software to decode a stream to chunks of raw decoded video and audio, main-taining synchronization (by inserting black fields or silence)
- Puffer - Stanford University
Puffer implements ABR on the server, so this pause was simulated to avoid introducing BOLA-specific logic in the server Specifically, the authors suggested that if all objectives are negative, BOLA-BASIC "v2" should choose the chunk with highest utility rather than highest objective
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