Expert judgment (or expert elicitation) is a formal process for eliciting judgments from subject-matter experts about the value of a decision-relevant quantity. Judgments in the form of subjective probability distributions are obtained from several experts, raising the question how best to combine information from multiple experts. A number of algorithmic approaches have been proposed, of which...

A new algorithm is proposed that performs competitive principal component analysis (PCA) of an image. A set of expert PCA networks compete, through the Mixture of Experts (MOE) formalism, on the basis of their ability to reconstruct the original image. The result is that the network finds an optimal projection of the image onto a reduced dimensional space as a function of the input and, hence, ...

A three-level hierarchical mixture model for classiŽcation is presented that models the following data generation process: (1) the data are generated by a Žnite number of sources (clusters), and (2) the generation mechanism of each source assumes the existence of individual internal class-labeled sources (subclusters of the external cluster). The model estimates the posterior probability of cla...

The trend in cache design research is towards finding the single optimum replacement policy that performs better than any other proposed policy by using all the useful criteria at once. However, due to the variety of workloads and system topologies it is daunting, if not impossible, to summarize all this information into one magical value using any static formula. We propose a workload and topo...

We compare expert finding approaches that use and combine different types of expertise evidence: content-based expert finding using academic papers, and expert finding using a social citation network between the documents and authors. We evaluate our approaches on a test collection that represents the research output of a typical average-sized academic workgroup. We find that expert finding usi...

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We address the expert crowdsourcing problem, in which an employer wishes to assign tasks to a set of available workers with heterogeneous working costs. Critically, as workers produce results of varying quality, the utility of each assigned task is unknown and can vary both between workers and individual tasks. Furthermore, in realistic settings, workers are likely to have limits on the number ...

Estimating motion in scenes containing multiple motions remains a diicult problem for computer vision. Here we describe a novel recurrent network architecture which solves this problem by simultaneously estimating motion and segmenting the scene. The network is comprised of locally connected units which carry out simple calculations in parallel. We present simulation results illustrating the su...

A three-level hierarchical mixture model for classification is presented that models the following data generation process: (1) the data are generated by a finite number of sources (clusters), and (2) the generation mechanism of each source assumes the existence of individual internal class-labeled sources (subclusters of the external cluster). The model estimates the posterior probability of c...