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Gauri Joshi

Researcher at Carnegie Mellon University

Publications -  117
Citations -  6938

Gauri Joshi is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Computer science & Stochastic gradient descent. The author has an hindex of 26, co-authored 91 publications receiving 3521 citations. Previous affiliations of Gauri Joshi include Massachusetts Institute of Technology & Indian Institute of Technology Bombay.

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Advances and open problems in federated learning

Peter Kairouz, +58 more
TL;DR: In this article, the authors describe the state-of-the-art in the field of federated learning from the perspective of distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, and statistics.
Proceedings Article

Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization

TL;DR: This paper provides the first principled understanding of the solution bias and the convergence slowdown due to objective inconsistency and proposes FedNova, a normalized averaging method that eliminates objective inconsistency while preserving fast error convergence.
Posted Content

Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms

TL;DR: This paper presents a unified framework called Cooperative SGD that subsumes existing communication-efficient SGD algorithms such as periodic-averaging, elastic-aversaging and decentralized SGD and provides novel convergence guarantees for existing algorithms.
Journal ArticleDOI

On the Delay-Storage Trade-Off in Content Download from Coded Distributed Storage Systems

TL;DR: This work uses a novel fork-join queueing framework to model multiple users requesting the content simultaneously, and derive bounds on the expected download time, demonstrating the fundamental trade-off between the expected downloading time and the amount of storage space.