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Representative points, which compact a probability distribution into a finite point set, are useful for a wide array of “small-data” and “big-data” problems. Small-data problems arise naturally in many engineering applications, where a key challenge is to allocate limited experimental runs for performing functional approximation, uncertainty propagation or design optimization. Similarly, given the massive volume, variety and velocity of big-data (particularly in Bayesian problems), the reduction of such datasets using representative points allows for meaningful and timely analysis. This working group aims to investigate the theory and application of representative points to the aforementioned small-data and big-data problems, with an emphasis on engineering applications and Bayesian computation.
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SAMSI Directorate Liaison: Ilse Ipsen
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