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Cocktail: Leveraging Ensemble Learning for Optimized Model Serving in Public Cloud., , , , and . CoRR, (2021)HoloAR: On-the-fly Optimization of 3D Holographic Processing for Augmented Reality., , , , , , , and . MICRO, page 494-506. ACM, (2021)Pushing Point Cloud Compression to the Edge., , , , , and . MICRO, page 282-299. IEEE, (2022)Usas: A Sustainable Continuous-Learning' Framework for Edge Servers., , , , and . HPCA, page 891-907. IEEE, (2024)An Efficient Edge-Cloud Partitioning of Random Forests for Distributed Sensor Networks., , , , and . IEEE Embed. Syst. Lett., 16 (1): 21-24 (March 2024)Implications of Public Cloud Resource Heterogeneity for Inference Serving., , , , and . WOSC@Middleware, page 7-12. ACM, (2020)Towards Designing a Self-Managed Machine Learning Inference Serving System inPublic Cloud., , , , and . CoRR, (2020)Cocktail: A Multidimensional Optimization for Model Serving in Cloud., , , , , and . NSDI, page 1041-1057. USENIX Association, (2022)MLPP: Exploring Transfer Learning and Model Distillation for Predicting Application Performance., and . NAS, page 1-4. IEEE, (2021)Origin: Enabling On-Device Intelligence for Human Activity Recognition Using Energy Harvesting Wireless Sensor Networks., , , and . DATE, page 1414-1419. IEEE, (2021)