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Simultaneous Sequential Detection of Multiple Interacting Faults
Simultaneous Sequential Detection Multiple Interacting Faults
2011/1/4
Single fault sequential change point problems have become important in modeling for various phenomena in large distributed systems, such as sensor networks. But such systems in many situations present...
Nonsmooth Formulation of the Support Vector Machine for a Neural Decoding Problem
Nonsmooth Formulation the Support Vector Machine Neural Decoding Problem
2011/1/4
This paper formulates a generalized classification algorithm with an application to classifying (or `decoding') neural activity in the brain. Medical doctors and researchers have long been interested ...
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Inverse Power Method Nonlinear Eigenproblems
2011/1/4
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding cri...
In applications throughout science and engineering one is often faced with the challenge of solving an ill-posed inverse problem, where the number of available measurements is smaller than the dimensi...
Feasibility and performances of compressed-sensing and sparse map-making with Herschel/PACS data
compressed-sensing sparse map-making Herschel/PACS data
2011/1/4
The Herschel Space Observatory of ESA was launched in May 2009 and is in operation since. From its distant orbit around L2 it needs to transmit a huge quantity of information through a very limited ba...
Quality of Source Location Protection in Globally Attacked Sensor Networks
Source Location Protection Globally Attacked Sensor Networks
2011/1/4
We propose an efficient scheme for generating fake network traffic to disguise the real event notification in the presence of a global eavesdropper, which is especially relevant for the quality of ser...
We study positive measures that are solutions to an abstract optimisation problem, which is a generalisation of a classical variational problem with a constraint on information of a Kullback-Leibler t...
Large-scale interval and point estimates from an empirical Bayes extension of confidence posteriors
Large-scale interval point estimates empirical Bayes
2011/1/4
The proposed approach extends the confidence posterior distribution to the semi-parametric empirical Bayes setting. Whereas the Bayesian posterior is defined in terms of a prior distribution condition...
Ordinal Discriminant Analysis: A new approach to the construction of optimal linear scores for ordinal risk categories
Ordinal Discriminant Analysis optimal linear scores ordinal risk categories
2011/1/4
Most classification methods provide either a prediction of group membership or an assessment of class membership probability. In the case of two-group classification the predicted probability can be d...
Sequential Monte Carlo (SMC) methods are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. We propose a new SMC algorithm to compute the expectation...
Approximate tail probabilities of the maximum of a chi-square field on multi-dimensional lattice points and their applications to detection of loci interactions
Approximate tail probabilities a chi-square field multi-dimensional lattice points
2011/1/4
Define a chi-square random field on a multi-dimensional lattice points index set with a direct-product covariance structure, and consider the distribution of the maximum of this random field. We provi...
Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes
Scalable Inference Customer Similarities Interactions Data Dirichlet Processes
2011/1/4
Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions among customers from...
We present a mixture Poisson model for claims counts in which the number of components in the mixture are estimated by reversible jump MCMC methods.
Discrimination for Two Way Models with Insurance Application
Two Way Models Insurance Application
2011/1/4
In this paper, we review and apply several approaches to model selection for analysis of variance models which are used in a credibility and insurance context. The reversible jump algorithm is employe...
Control of the False Discovery Rate Under Arbitrary Covariance Dependence
Rate Covariance Dependence
2011/1/4
Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are...