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Week of February 6 - February 10, 2017:
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ICME Weekly Seminar Digest

Please click here for upcoming seminar information as well as other events going on in ICME.
MONDAY, FEBRUARY 6, 2017
CME 500: Departmental Seminar
Speaker: Enguerrand Horel, ICME student

Title: Interpretation of neural networks and application in finance

Abstract: Although neural networks can can achieve a high predictive accuracy rate, their intrinsically lack of interpretability has prevented them from being successfully applied in a financial setting. In this presentation, we will first present the objectives of interpretability and defines what makes a model interpretable. The problems of neural network's architecture selection and identification and its implication to interpretability will then be considered. Finally, we will review existing interpretation methods and mention potential new approaches. 
 
Time: 4:30-5:20 p.m.
Location: Hewlett 102
TUESDAY, FEBRUARY 7, 2017
CME 300: First Year Seminar Series
Speaker: Michael Saunders, Professor Emeritus, MS&E and ICME

Title: Linear algebra and optimization software at Systems Optimization Laboratory (SOL)

Abstract: The Systems Optimization Laboratory (http://stanford.edu/group/SOL) promotes the development and application of reliable numerical methods for solving large-scale systems of equations and constrained optimization problems.  We give an overview of the algorithms available and some interesting applications (including aerospace).

Time: 12:30-1:20 p.m.
Location: Y2E2-101
THURSDAY, FEBRUARY 9, 2017
CME 510: Linear Algebra and Optimization Seminar
Speaker: Dr. Youngsoo Choi, Sandia National Laboratories, Livermore

Title: Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction

Abstract: Reduced-order models (ROMs) of nonlinear dynamical systems are essential for enabling high-fidelity computational models to be used in many-query and real-time applications such as uncertainty quantification and design optimization.  Such ROMs reduce the dimensionality of the dynamical system by executing a projection process on the governing system of nonlinear ordinary differential equations.  The resulting ROM can then be numerically integrated in time.  Unfortunately, many applications require resolving the model over long time intervals, leading to a large number of time instances at which the fully discretized model must be resolved.  The number of time instances required for the ROM simulation remains large, which can limit its computational savings.

We will go over ROMs for nonlinear dynamical systems.  Especially, a novel space-time ROM will be introduced.  The model applies space-time least-squares Petrov-Galerkin projection to decrease both spatial and temporal complexity.  An error bound with a slow growth rate and numerical results show its strength and advantage over traditional ROMs.

Time: 4:30-5:30 p.m.
Location: Y2E2-101
OTHER ICME RELATED SEMINARS:
Applied Math Seminar

Visit their seminars page at mathematics.stanford.edu for updates.
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