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20192025
most citedSquirRL: Automating Attack Analysis on Blockchain Incentive Mechanisms with Deep Reinforcement Learning

21 citations · 34 across the 8 of their papers we have counts for

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Showing 2021Show all

2 papers · 1 filter

cs.LG2021★ 2 cited

FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning

Charlie Hou, Kiran K. Thekumparampil, Giulia Fanti +1

Federated learning (FL) aims to minimize the communication complexity of training a model over heterogeneous data distributed across many clients. A common approach is local method…

cs.LG2021★ 9 cited

Efficient Algorithms for Federated Saddle Point Optimization

Charlie Hou, Kiran K. Thekumparampil, Giulia Fanti +1

We consider strongly convex-concave minimax problems in the federated setting, where the communication constraint is the main bottleneck. When clients are arbitrarily heterogeneous…