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Stats, Optimization, and Machine Learning Seminar - Paul Constantine
Start Date: 3/21/2017Start Time: 3:30 PM
End Date: 3/21/2017End Time: 4:30 PM
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Event Description:
Paul Constantine, Department of Applied Mathematics and Statistics, Colorado School of Mines 
Active Subspaces: Emerging Ideas for Dimension Reduction in Computational Science and Engineering Models
Scientists and engineers use computer simulations to study relationships between a physical model's input parameters and its output predictions. However, thorough parameter studies -- e.g., constructing response surfaces, optimizing or averaging -- are challenging, if not impossible, when the simulation is expensive and the model has several inputs. To enable parameter studies in these cases, the engineer may attempt to reduce the dimension of the model's input parameter space. Active subspaces are part of an emerging set of subspace-based dimension reduction tools that identify important directions in the input parameter space. Constantine will (i) describe computational methods for discovering a model's active subspaces, (ii) propose strategies for exploiting the reduced dimension to enable otherwise infeasible parameter studies, and (iii) review results from several science and engineering applications. For more information, visit 
Location Information:
Main Campus - Discovery Learning Center  (View Map)
Boulder, CO
Contact Information:
Name: Ian Cunningham
Phone: 303-492-4668

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