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Machine Learning on Volatile Instances: Convergence, Runtime, and Cost Tradeoffs., , , , , , and . IEEE/ACM Trans. Netw., 30 (1): 215-228 (2022)Plan B: Design Methodology for Cyber-Physical Systems Robust to Timing Failures., , , , , , , , , and 1 other author(s). ACM Trans. Cyber Phys. Syst., 6 (3): 21:1-21:39 (2022)On Merits and Viability of Multi-Cloud Serverless., , , and . SoCC, page 600-608. ACM, (2021)Can we Generalize and Distribute Private Representation Learning?, , , , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 11320-11340. PMLR, (2022)Demo: enabling mobile time-dependent pricing., , , , and . MobiSys, page 473-474. ACM, (2012)Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies., , , , and . INFOCOM, page 2762-2770. IEEE, (2018)Optimized Day-Ahead Pricing for Smart Grids with Device-Specific Scheduling Flexibility., , , and . IEEE J. Sel. Areas Commun., 30 (6): 1075-1085 (2012)Vehicle dispatching for sensing coverage optimization in mobile crowdsensing systems: poster abstract., , , , , and . IPSN, page 311-312. ACM, (2019)AMUSE: Empowering Users for Cost-Aware Offloading with Throughput-Delay Tradeoffs., , , , , and . CoRR, (2017)AdaCoOpt: Leverage the Interplay of Batch Size and Aggregation Frequency for Federated Learning., , , , , and . IWQoS, page 1-10. IEEE, (2023)