We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Abstract--In this paper we propose a probabilistic classification algorithm with a novel Dynamic Time Warping (DTW) kernel to automatically recognize flight calls of different spec...
Theodoros Damoulas, Samuel Henry, Andrew Farnswort...
A new strategy is proposed for the design of cascaded object detectors of high detection-rate. The problem of jointly minimizing the false-positive rate and classification complex...
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...