Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated...
In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own m...
We study the implication that various timeliness and failure detector assumptions have on the performance of consensus algorithms that exploit them. We present a general framework...
Consensus is one of the most fundamental problems in fault-tolerant distributed computing. This paper proposes a mechanical method for analyzing the condition that allows one to s...
RANSAC (Random Sample Consensus) is a popular and effective technique for estimating model parameters in the presence of outliers. Efficient algorithms are necessary for both fram...
Paul McIlroy, Edward Rosten, Simon Taylor, Tom Dru...