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20072022
most citedBreaking the O(n^2) Bit Barrier: Scalable Byzantine agreement with an Adaptive Adversary

46 citations · 67 across the 18 of their papers we have counts for

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6 papers · 1 filter

cs.DS2022

Computing (1+epsilon)-Approximate Degeneracy in Sublinear Time

Valerie King, Alex Thomo, Quinton Yong

The problem of finding the degeneracy of a graph is a subproblem of the k-core decomposition problem. In this paper, we present a (1 + epsilon)-approximate solution to the degenera…

cs.DS2018★ 1 cited

A Deterministic Distributed Algorithm for Exact Weighted All-Pairs Shortest Paths in Rounds

Udit Agarwal, Vijaya Ramachandran, Valerie King +1

We present a deterministic distributed algorithm to compute all-pairs shortest paths(APSP) in an edge-weighted directed or undirected graph. Our algorithm runs in $\tilde{O}(n^{3/2…

cs.DS2015

Dynamic graph connectivity with improved worst case update time and sublinear space

David Gibb, Bruce Kapron, Valerie King +1

This paper considers fully dynamic graph algorithms with both faster worst case update time and sublinear space. The fully dynamic graph connectivity problem is the following: give…

cs.DS2013★ 2 cited

Quorums Quicken Queries: Efficient Asynchronous Secure Multiparty Computation

Varsha Dani, Valerie King, Mahnush Movahedi +1

We describe an asynchronous algorithm to solve secure multiparty computation (MPC) over n players, when strictly less than a 1/8 fraction of the players are controlled by a static…

cs.DS2012

Secure Multi-Party Computation in Large Networks

Varsha Dani, Valerie King, Mahnush Movahedi +2

We describe scalable protocols for solving the secure multi-party computation (MPC) problem among a large number of parties. We consider both the synchronous and the asynchronous c…

cs.DS2007

Sleeping on the Job: Energy-Efficient Broadcast for Radio Networks

Valerie King, Cynthia Phillips, Jared Saia +1

We address the problem of minimizing power consumption when performing reliable broadcast on a radio network under the following popular model. Each node in the network is located…