Pages that link to "Item:Q911463"
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The following pages link to On the limited memory BFGS method for large scale optimization (Q911463):
Displaying 50 items.
- Approximate ADMM algorithms derived from Lagrangian splitting (Q1687316) (← links)
- Machine learning of linear differential equations using Gaussian processes (Q1694641) (← links)
- On the nonmonotonicity degree of nonmonotone line searches (Q1697277) (← links)
- Hidden physics models: machine learning of nonlinear partial differential equations (Q1699464) (← links)
- Reconstruction of recurrent synaptic connectivity of thousands of neurons from simulated spiking activity (Q1704910) (← links)
- Investigation of the sampling performance of ensemble-based methods with a simple reservoir model (Q1705872) (← links)
- Speckle reduction with trained nonlinear diffusion filtering (Q1708000) (← links)
- Multi-step spectral gradient methods with modified weak secant relation for large scale unconstrained optimization (Q1713247) (← links)
- A study of structure-exploiting SQP algorithms for an optimal control problem with coupled hyperbolic and ordinary differential equation constraints (Q1713287) (← links)
- Dropout training for SVMs with data augmentation (Q1713848) (← links)
- A limited-memory optimization method using the infinitely many times repeated BNS update and conjugate directions (Q1715789) (← links)
- Improved optimization methods for image registration problems (Q1717565) (← links)
- The adjoint method for the inverse problem of option pricing (Q1718099) (← links)
- Multigrid optimization for DNS-based optimal control in turbulent channel flows (Q1721836) (← links)
- A new modified three-term Hestenes-Stiefel conjugate gradient method with sufficient descent property and its global convergence (Q1722876) (← links)
- A fractal shape optimization problem in branched transport (Q1726952) (← links)
- Conditional random fields for pattern recognition applied to structured data (Q1736677) (← links)
- Hessian-based covariance approximations in variational data assimilation (Q1742001) (← links)
- A new supermemory gradient method for unconstrained optimization problems (Q1758038) (← links)
- An optimization approach to the problem of protein structure prediction (Q1764247) (← links)
- An iterative global optimization algorithm for potential energy minimization (Q1774569) (← links)
- Numerical experimentsregarding the distributed control of semilinear parabolic problems (Q1779590) (← links)
- A linearized and incompressible constitutive model for arteries (Q1786381) (← links)
- Space-dependent Sobolev gradients as a regularization for inverse radiative transfer problems (Q1793010) (← links)
- Tensors, differential geometry and statistical shading analysis (Q1799554) (← links)
- Distances and means of direct similarities (Q1799949) (← links)
- Relatively-paired space analysis: learning a latent common space from relatively-paired observations (Q1799958) (← links)
- Optimal control of flow with discontinuities. (Q1811663) (← links)
- On the resolution of monotone complementarity problems (Q1815077) (← links)
- Variational assimilation of oceanographic data. Primal and dual approaches (Q1826245) (← links)
- On the smoothness constraints for four-dimensional data assimilation (Q1851281) (← links)
- A numerical study of limited memory BFGS methods (Q1861792) (← links)
- Optimal control of cylinder wakes via suction and blowing (Q1869307) (← links)
- A truncated Newton optimization algorithm in meteorology applications with analytic Hessian/vector products (Q1892597) (← links)
- Local search based heuristics for global optimization: atomic clusters and beyond (Q1926903) (← links)
- Fitting very large sparse Gaussian graphical models (Q1927038) (← links)
- Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling (Q1927096) (← links)
- Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization (Q1938913) (← links)
- Accelerated linearized Bregman method (Q1945379) (← links)
- Iterative diagonalization of symmetric matrices in mixed precision and its application to electronic structure calculations (Q1948839) (← links)
- Improved Hessian approximations for the limited memory BFGS method (Q1964059) (← links)
- IMAS. Integrated modeling and analysis system for the solution of optimal control problems (Q1967214) (← links)
- Multiscale topology optimization using neural network surrogate models (Q1986944) (← links)
- Machine learning in drug development: characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification (Q1987901) (← links)
- Parallel two-phase methods for global optimization on GPU (Q1997322) (← links)
- Two--parameter scaled memoryless BFGS methods with a nonmonotone choice for the initial step length (Q2009059) (← links)
- Surface reconstruction by parallel and unified particle-based resampling from point clouds (Q2010272) (← links)
- Semi-idealized study on estimation of partly and fully space varying open boundary conditions for tidal models (Q2015315) (← links)
- A Newton-like trust region method for large-scale unconstrained nonconvex minimization (Q2015579) (← links)
- Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization (Q2020786) (← links)
