Nonlinear splitting of gradients and constraints yields semi-implicit gradient methods and cheaper adjoint gradients, demonstrated on nonconvex benchmarks, quantum tomography, and kinetic transport.
A differential-equations algorithm for nonlinear equations.ACM Transactions on Mathematical Software (TOMS), 10(3):299–316,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
math.OC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
Nonlinear Splitting for Gradient-Based Unconstrained and Adjoint Optimization
Nonlinear splitting of gradients and constraints yields semi-implicit gradient methods and cheaper adjoint gradients, demonstrated on nonconvex benchmarks, quantum tomography, and kinetic transport.