SHOPPING CART $0.00
free shipping on orders over $35*
BUYBACK CART Buyback Cart Total Buyback Cart Total
free shipping on buybacks!
loading

    Recent Advances in Algorithmic Differentiation

    ISBN-10: 3642300227
    ISBN-13: 9783642300226
    Author(s): Shaun Forth, Paul Hovland, Eric Phipps, Jean Utke, Andrea Walther
    Description: The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of  More...
    Buy it from: $170.96

    Order within the next: to receive same day shipping!

    Loading
    Customers Also Bought

    Publisher: Springer
    Binding: Hardcover
    Pages: 362
    Size: 6.25" wide x 9.25" long x 1.00" tall
    Weight: 1.496
    Language: English

    The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of AD theory and its implementation in tools. For all papers the referees, selected from the program committee and the greater community, as well as the editors have emphasized accessibility of the presented ideas also to non-AD experts. In the AD tools arena new implementations are introduced covering, for example, Java and graphical modeling environments or join the set of existing tools for Fortran. New developments in AD algorithms target the efficiency of matrix-operation derivatives, detection and exploitation of sparsity, partial separability, the treatment of nonsmooth functions, and other high-level mathematical aspects of the numerical computations to be differentiated. Applications stem from the Earth sciences, nuclear engineering, fluid dynamics, and chemistry, to name just a few. In many cases the applications in a given area of science or engineering share characteristics that require specific approaches to enable AD capabilities or provide an opportunity for efficiency gains in the derivative computation. The description of these characteristics and of the techniques for successfully using AD should make the proceedings a valuable source of information for users of AD tools.

    Buy it from $170.96

    Please choose a buying option

    Your Price:
    You save:
    Buy It Now
    what's this?
    Rush Rewards U
    Members Receive:
    coins
    coins
    You have reached 400 XP and carrot coins. That is the daily max!
    ×
    Free shipping on orders over $35*

    *A minimum purchase of $35 is required. Shipping is provided via FedEx SmartPost® and FedEx Express Saver®. Average delivery time is 1 – 5 business days, but is not guaranteed in that timeframe. Also allow 1 - 2 days for processing. Free shipping is eligible only in the continental United States and excludes Hawaii, Alaska and Puerto Rico. FedEx service marks used by permission."Marketplace" orders are not eligible for free or discounted shipping.

    Learn more about the TextbookRush Marketplace.

    ×