Content providers are increasingly using data-driven mechanisms to optimize quality of
experience (QoE). Many existing approaches formulate this process as a prediction problem of …

Many prior efforts have suggested that Internet video Quality of Experience (QoE) could be
dramatically improved by using data-driven prediction of video quality for different choices (eg…

Recently, machine learning has been used in every possible field to leverage its amazing
power. For a long time, the networking and distributed computing system is the key …

Many commercial video players rely on bitrate adaptation logic to adapt the bitrate in response
to changing network conditions. Past measurement studies have identified issues with …

Edge video analytics is becoming the solution to many safety and management tasks. Its
wide deployment, however, must first address the tension between inference accuracy and …

Applying deep convolutional neural networks (NN) to video data at scale poses a substantial
systems challenge, as improving inference accuracy often requires a prohibitive cost in …

Bitrate adaptation is critical in ensuring good users’ quality-of-experience (QoE) in Internet
video delivery system. Several efforts have argued that accurate throughput prediction can …

Video traffic already represents a significant fraction of today's traffic and is projected to
exceed 90% in the next five years. In parallel, user expectations for a high quality viewing …

… In this project, Junchen Jiang and Kuntai Du are supported by NSF (CNS-1901466). Junchen
Jiang is also supported by Google Faculty Research Award. Moreover, Ahsan Pervaiz and …

Video analytics applications use edge compute servers for processing videos. Compressed
models that are deployed on the edge servers for inference suffer from data drift where the …