ملف الباحث
Konstantin Burlachenko
ورقتان في مجموعة PaperMetrix
المنشورات
أوراق هذا المؤلف
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MARINA: Faster Non-Convex Distributed Learning with Compression
2021 · arXiv (Cornell University)
We develop and analyze MARINA: a new communication efficient method for non-convex distributed learning over heterogeneous datasets. MARINA employs a novel communication compression strategy based on the compression of gradient differences that is reminiscent of …
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Federated Learning with Regularized Client Participation
2023 · arXiv (Cornell University)
Federated Learning (FL) is a distributed machine learning approach where multiple clients work together to solve a machine learning task. One of the key challenges in FL is the issue of partial participation, which occurs …