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Breaking (Global) Barriers in Parallel Stochastic Optimization With Wait-Avoiding Group Averaging.

, , , , , , and . IEEE Trans. Parallel Distributed Syst., 32 (7): 1725-1739 (2021)

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PopSGD: Decentralized Stochastic Gradient Descent in the Population Model., , , , , and . CoRR, (2019)The Transactional Conflict Problem., , , and . SPAA, page 383-392. ACM, (2018)Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent., , , , and . AAAI, page 9037-9045. AAAI Press, (2021)Efficiency Guarantees for Parallel Incremental Algorithms under Relaxed Schedulers., , and . CoRR, (2020)QuAFL: Federated Averaging Can Be Both Asynchronous and Communication-Efficient., , , and . CoRR, (2022)Dynamic Averaging Load Balancing on Cycles., , and . ICALP, volume 168 of LIPIcs, page 7:1-7:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2020)The Power of Choice in Priority Scheduling., , , and . PODC, page 283-292. ACM, (2017)Relaxed Schedulers Can Efficiently Parallelize Iterative Algorithms., , , and . PODC, page 377-386. ACM, (2018)On approximating strip packing with a better ratio than 3/2., and . SODA, page 1491-1510. SIAM, (2016)Asynchronous Decentralized SGD with Quantized and Local Updates., , , , and . NeurIPS, page 6829-6842. (2021)