Good morning CPS,

Today’s Division Meeting will include a talk by Krishna Narayanan and Jan Hueckelheim of the MCS Division. The talk, titled “Using Algorithmic Differentiation Tools to Compute Derivatives” will be presented at 2:00 PM via BlueJeans.

Abstract: Algorithmic or automatic, differentiation (AD or autodiff)  is a technique for transforming algorithms that compute some mathematical function into algorithms that compute the derivatives of that function. AD techniques combine rules for differentiating the functions intrinsic to a given programming language with strategies for applying the chain rule.  AD has been used extensively for computing derivatives that are used for sensitivity analysis, optimization, parameter (state) estimation etc. Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning as well.

Monday, November 16 @ 2:00 PM

Join Meeting

+1.408.317.9254 (US (San Jose))
+1.866.226.4650 (US Toll Free)
(Global Numbers)
Meeting ID: 919 103 457

The CPS Division seminar schedule is available here.

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Samantha L Tezak

Executive Assistant, CPS Division

Argonne National Laboratory

9700 S. Cass Avenue

Lemont, IL 60439

Tel:  (630) 252-6250

E-mail: stezak@anl.gov

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