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Published in NeurIPS 2024, 2024
We consider nonconvex stochastic optimization problems in the asynchronous centralized distributed setup where the communication times from workers to a server can not be ignored, and the computation and communication times are potentially different for all workers. Using an unbiassed compression technique, we develop a new method-Shadowheart SGD-that provably improves the time complexities of all previous centralized methods. Moreover, we show that the time complexity of Shadowheart SGD is optimal in the family of centralized methods with compressed communication. We also consider the bidirectional setup, where broadcasting from the server to the workers is non-negligible, and develop a corresponding method.
Recommended citation: https://arxiv.org/abs/2402.04785
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Undergraduate course, Bocconi University, 2022
Statistics (30001) is a 2nd year course for the students enrolled in the BIEM and CLEF classes at Bocconi University. It introduces the basic of descriptive statistics and inference. I have been the TA of this course for the classes CLEF9 and CLEF10.