Motivation For streaming applications,adaptive network strategies may involve a combination of dynamic bitrate allocation along with playback interruptions when the available bandwidth reaches a very low value. Propose Video Assessment of TemporaL Artifacts and Stalls (Video ATLAS):a machine learning framework where we combine a number of QoE-related features,including objective quality features,rebuffering- aware features and memory-driven features to make QoE predictions.Motivation For streaming applications, adaptive network strategies may involve a combination of dynamic bitrate allocation along with playback interruptions when the available bandwidth reaches a very low value. Propose Video Assessment of TemporaLArtifacts and Stalls (Video ATLAS): a machine learning framework where we combine a number of QoE-related features, including objective quality features, rebuffering￾aware features and memory-driven features to make QoE predictions