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We consider the problem of detecting the periodic part of a function given the observations of some input/output tuples (xi,yi). As they are known for being powerful tools for dealing with such data, ...
Network detection is an important capability in many areas of applied research in which data can be represented as a graph of entities and relationships. Oftentimes the object of interest is a relativ...
Community detection can be considered as a variant of cluster analysis applied to complex networks. For this reason, all existing studies have been using tools derived from this field when evaluating ...
Non-stationarity of the event rate is a persistent problem in modeling time series of events, such as neuronal spike trains. Motivated by a variety of patterns in neurophysiological spike train record...
Recently, the deep-belief-networks (DBN) based voice activity detection (VAD) has been proposed. It is powerful in fusing the advantages of multiple features, and achieves the state-of-the-art perform...
We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class su...
In the classical version of the Bayesian quickest change detection problem proposed by Shiryaev, there is a sequence of observations whose distribution changes at a random time, and the goal is to m...

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