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  • title: Acceleration for Compressed Gradient Descent in Distributed Optimization
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            Acceleration for Compressed Gradient Descent in Distributed Optimization
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            Acceleration for Compressed Gradient Descent in Distributed Optimization

            Jul 12, 2020

            Speakers

            ZL

            Zhize Li

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            DK

            Dmitry Kovalev

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            XQ

            Xun Qian

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            About

            Due to the high communication cost in distributed and federated learning problems, methods relying on sparsification or quantization of communicated messages are becoming increasingly popular. While in other contexts the best performing gradient-type methods invariably rely on some form of acceleration to reduce the number of iterations, there are no methods which combine the benefits of both gradient compression and acceleration. In this paper, we remedy this situation and propose the first acc…

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            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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