Saurav Prakash
Saurav Prakash
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Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training
Detection and mitigation of Byzantine behaviors in a decentralized learning setting is a daunting task, especially when the data …
Ahmed Roushdy Elkordy
,
Saurav Prakash
,
Salman Avestimehr
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CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning
We focus on the commonly used synchronous Gradient Descent paradigm for large-scale distributed learning, for which there has been a …
Amirhossein Reisizadeh
,
Saurav Prakash
,
Ramtin Pedarsani
,
Salman Avestimehr
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Coded computing for low-latency federated learning over wireless edge networks
Federated learning enables training a global model from data located at the client nodes, without data sharing and moving client data …
Saurav Prakash
,
Sagar Dhakal
,
Mustafa Akdeniz
,
Yair Yona
,
Shilpa Talwar
,
Salman Avestimehr
,
Nageen Himayat
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Coded computing for distributed graph analytics
Many distributed computing systems have been developed recently for implementing graph based algorithms such as PageRank over …
Saurav Prakash
,
Amirhossein Reisizadeh
,
Ramtin Pedarsani
,
Salman Avestimehr
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DOI
Coded computation over heterogeneous clusters
In large-scale distributed computing clusters, such as Amazon EC2, there are several types of “system noise” that can …
Amirhossein Reisizadeh
,
Saurav Prakash
,
Ramtin Pedarsani
,
Salman Avestimehr
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