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Continuous Learning for Lightweight Machine Learning Inference at the Edge. MIT, USA, (2023)Gemino: Practical and Robust Neural Compression for Video Conferencing., , , , , , , и . CoRR, (2022)Gemino: Practical and Robust Neural Compression for Video Conferencing., , , , , , , и . NSDI, стр. 569-590. USENIX Association, (2024)End-to-end transport for video QoE fairness., , , , , и . SIGCOMM, стр. 408-423. ACM, (2019)SiP-ML: high-bandwidth optical network interconnects for machine learning training., , , , , , , , и . SIGCOMM, стр. 657-675. ACM, (2021)Temporal Dynamics of Connectivity and Epidemic Properties of Growing Networks., и . CoRR, (2015)RECL: Responsive Resource-Efficient Continuous Learning for Video Analytics., , , , , , , и . NSDI, стр. 917-932. USENIX Association, (2023)Exploiting Channel Locality for Adaptive Massive MIMO Signal Detection., , , и . ICASSP, стр. 8565-8568. IEEE, (2020)Efficient Video Compression via Content-Adaptive Super-Resolution., , и . ICCV, стр. 4501-4510. IEEE, (2021)Real-Time Video Inference on Edge Devices via Adaptive Model Streaming., , , и . ICCV, стр. 4552-4562. IEEE, (2021)