Biomolex has technology for real-time imaging of radioactive emissions. Images are acquired for measuring radioactivity in tissue slices for assessing transport and uptake of labeled biomolecules or in spots in protein kinase arrays for evaluating protein phosphorylations. The sensor used is a silicon strip detector, and a problem is that some strips produce no signal. Also, some other strips m...

Searching for services often starts from the exploration of the service space. Community generated tags can support such exploration. Researchers attracted by the community-available “free manpower” proposed more complex tagging models. Those models tag specific parts of the Web service definition: single operations, their inputs and outputs. However, there is no evidence whether the annotation...

We propose a novel semi-supervised structured output prediction method based on local linear regression in this paper. The existing semi-supervise structured output prediction methods learn a global predictor for all the data points in a data set, which ignores the differences of local distributions of the data set, and the effects to the structured output prediction. To solve this problem, we ...

During the last four decades Data Envelopment Analysis DEA has attracted considerable attention in the OR community. Using DEA, the efficiency frontier is constructed based on assumptions concerning the production possibility set rather than a priori defining a functional relationship between inputs and outputs. In this contribution, we propose an algorithm to visualize the efficiency surface i...

The data model of independent component analysis (ICA) gives a multivariate probability density that describes many kinds of sensory data better than classical models like Gaussian densities or Gaussian mixtures. When only a subset of the random variables is observed, ICA can be used for regression, i.e. to predict the missing observations. In this paper, we show that the resulting regression i...

If the data vector for input to an automatic classifier is incomplete, the optimal estimate for each class probability must be calculated as the expected value of the classifier output. We identify a form of Radial Basis Function (RBF) classifier whose expected outputs can easily be evaluated in terms of the original function parameters. Two ways are described in which this classifier can be ap...

We describe an algorithm to estimate the pose of a generic articulated object. Our algorithm takes as input a description of the object and a potentially incomplete series of observations; it outputs an on-line estimate of the object’s configuration. This task is challenging because: (1) the distribution of object states is often multi-modal; (2) the object is not assumed to be under our contro...

Many classiication algorithms are \passive", in that they assign a class-label to each instance based only on the description given, even if that description is incomplete. In contrast , an active classiier can | at some cost | obtain the values of missing attributes, before deciding upon a class label. The expected utility of using an active classiier depends on both the cost required to obtai...

Label switching is a well-known phenomenon that occurs in MCMC outputs targeting the parameters’ posterior distribution of many latent variable models. Although its appearence is necessary for the convergence of the simulated Markov chain, it turns out to be a problem in the estimation procedure. In a recent paper, Papastamoulis and Iliopoulos (2010) introduced the Equivalence Classes Represent...