Publication: Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation
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Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation

- Proceeding -
 

Author(s)

Editor(s)
Bruce Christianson, Shaun A. Forth, Andreas Griewank

Year
2018

Publisher
Taylor & Francis

AD Theory and Techniques
General

Contained Articles
- A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning
- A one-shot optimization framework with additional equality constraints applied to multi-objective aerodynamic shape optimization
- A usability case study of algorithmic differentiation tools on the ISSM ice sheet model
- Algorithmic differentiation for piecewise smooth functions: a case study for robust optimization
- Arbogast: Higher order automatic differentiation for special functions with Modular C
- Branch-locking AD techniques for nonsmooth composite functions and nonsmooth implicit functions
- Comparing high-order multivariate AD methods
- Computationally relevant generalized derivatives: theory, evaluation and applications
- Differentiating through conjugate gradient
- Divide-and-conquer checkpointing for arbitrary programs with no user annotation
- Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C
- Enumeration of subdifferentials of piecewise linear functions with abs-normal form
- Estimating the expansion coefficients of a geomagnetic field model using first-order derivatives of associated Legendre functions
- Expression templates for primal value taping in the reverse mode of algorithmic differentiation
- How AD can help solve differential-algebraic equations
- Integrating Lipschitzian dynamical systems using piecewise algorithmic differentiation
- Mathematically rigorous global optimization in floating-point arithmetic
- Mixed-language automatic differentiation
- Newton step methods for AD of an objective defined using implicit functions
- On efficient Hessian computation using the edge pushing algorithm in Julia
- On lower bounds for optimal Jacobian accumulation
- Optimization of triple-ring electrodes on piezoceramic transducers using algorithmic differentiation
- Parallelizable adjoint stencil computations using transposed forward-mode algorithmic differentiation
- Pattern graph for sparse Hessian matrix determination
- Piecewise linear secant approximation via algorithmic piecewise differentiation
- Preface
- Proximal gradient method with automatic selection of the parameter by automatic differentiation
- SIMPLE adjoint message passing
- Solving parameter estimation problems with discrete adjoint exponential integrators
- Source-to-source adjoint Algorithmic Differentiation of an ice sheet model written in C
- Towards a full higher order AD-based continuation and bifurcation framework
- Using automatic differentiation for compressive sensing in uncertainty quantification
- Validated computation of the local truncation error of Runge--Kutta methods with automatic differentiation

BibTeX
@PROCEEDINGS{
         Christianson2018Sio,
       title = "Special issue of Optimization Methods \& Software: Advances in Algorithmic
         Differentiation",
       editor = "Bruce Christianson and Shaun A. Forth and Andreas Griewank",
       year = "2018",
       publisher = "Taylor \& Francis",
       ad_theotech = "General"
}


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