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  • title: Personalized Federated Learning with First Order Model Optimization
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            Personalized Federated Learning with First Order Model Optimization
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            Personalized Federated Learning with First Order Model Optimization

            May 3, 2021

            Speakers

            MJZ

            Michael J.Q. Zhang

            Speaker · 0 followers

            KS

            Karan Sapra

            Speaker · 0 followers

            SF

            Sanja Fidler

            Speaker · 2 followers

            About

            While federated learning traditionally aims to train a single global model across decentralized local datasets, one model may not always be ideal for all participating clients. Here we propose an alternative, where each client only federates with other relevant clients to obtain a stronger model per client-specific objectives. To achieve this personalization, rather than computing a single model average with constant weights for the entire federation as in traditional FL, we efficiently calculat…

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            I2

            ICLR 2021

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            AI & Data Science

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            About ICLR 2021

            The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning. ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.

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