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The increasing complexity of computer networks and our increasing dependence on them means enforcing reliability requirements is both more challenging and more critical. The expansion of network servi...
A topological multiple testing approach to peak detection is proposed for the problem of detecting transcription factor binding sites in ChIP-Seq data. After kernel smoothing of the tag counts over th...
For multivariate continuous data, the contaminated Gaussian distribution - having two parameters indicating the proportion of outliers and the degree of contamination - represents a convenient and nat...
This paper considers sparse spiked covariance matrix models in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minima...
This paper considers sparse spiked covariance matrix models in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minima...
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...
This paper introduces a spatio-temporal resonator model and an inference method for detection and estimation of nearly periodic temporal phenomena in spatio-temporal data. The model is derived as a sp...
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...
We consider the testing and estimation of change-points -- locations where the distribution abruptly changes -- in a data sequence. A new approach, based on scan statistics utilizing graphs representi...
The Interbank Offered Rate is a vital benchmark interest rate in the financial markets of every country to which financial contracts are tied. In the light of the recent LIBOR manipulation incident, t...
The Interbank Offered Rate is a vital benchmark interest rate in the financial markets of every country to which financial contracts are tied. In the light of the recent LIBOR manipulation incident, t...

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