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  • Stanford University - 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
    I am currently located in the United States Log in
  • Puffer - Stanford University
    The Website will stream live broadcast signals that the Stanford research team receives from our local digital antenna in Stanford, CA, to the study participants without any modification whatsoever to the programing content
  • 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
    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): 2026-03-30T11_2026-03-31T11 (share a permalink) Full results: Storage bucket Retrained model: 20260330-1 tar gz video_sent measurement: video
  • Learning in situ: a randomized experiment in . . . - Stanford University
    A Stanford Institutional Review Board determined that Puffer does not constitute human subjects research Our reasoning for streaming live television was to collect data from enough participants and network paths to draw robust conclusions about the performance of algorithms for ABR control and network prediction
  • 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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