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We describe a method for aligning multiple unlabeled configurations simultane- ously. Specifically, we extend the two-configuration matching approach of Green and Mardia (2006) to the multiple configuration setting. Our approach is based on the in- troduct ...
The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, ...
Structural investigations of several minerals belonging to the calaverite group with composition Au1–xAgxTe2 (x = 0.00, 0.02, 0.05, 0.09, 0.19, and 0.33) indicate that Ag is randomly distributed on the Au sites. This suppresses the valence fluctuation of A ...
We study bounding approximations for a multistage stochastic program with expected value constraints. Two simpler approximate stochastic programs, which provide upper and lower bounds on the original problem, are obtained by replacing the original stochast ...
Seaport container terminals are source of many interesting large-scale optimization problems, which arise in the management of operations at several decision levels. In this paper we firstly illustrate a recently proposed framework, called two-stage column ...
We present a method for dynamically integrating audio-visual information for speech recognition, based on the estimated reliability of the audio and visual streams. Our method uses an information theoretic measure, the entropy derived from the state probab ...
We formulate the service composition problem as a multi-objective stochastic program which simultaneously optimizes the following quality of service (QoS) parameters: workflow duration, service invocation costs, availability, and reliability. All of these ...
This paper focuses on the estimation of credence in the correctness of classification decisions produced by a biometric identity verification system. We adopt the concept of decision credence defined in terms of subjective Bayesian degree of belief. We dem ...
Multistage stochastic programs have applications in many areas and support policy makers in finding rational decisions that hedge against unforeseen negative events. In order to ensure computational tractability, continuous-state stochastic programs are us ...
We outline how modern likelihood theory, which provides essentially exact inferences in a variety of parametric statistical problems, may routinely be applied in practice. Although the likelihood procedures are based on analytical asymptotic approximations ...
