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Rockafellar [21, 22] studied fundamental duality theory for convex programs using a conjugate function and established a generalized version of the Fenchelís duality theorem.
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Maximum of the likelihood function are computed using a conjugate gradient method.
Finally, the minimization was done using a conjugate gradient algorithm.
Finally, the system was relaxed using a conjugate gradient algorithm.
The nonlinear convection problem is solved using a least-squares conjugate gradient algorithm, and the Stokes-like problem is solved using a conjugate gradient algorithm.
The compounds were prepared using a conjugate-based strategy.
In [10], they also obtained the result for a conjugate function by using the corresponding Nörlund means.
We also show that this function does not admit a conjugate function.
In the paper entitled "Iterative estimation algorithms using conjugate function lower bound and minorization-maximization with applications in image denoising," G. Deng and W.-Y. Ng propose a generalized algorithm for wavelet domain image denoising by solving the MAP estimation problems under a linear Gaussian observation model.
For each target, 50 initial models were generated and subsequently refined with two cycles of optimization, which undergoes 300 iterations of conjugate gradients using a variable-target function method and molecular dynamics with simulated annealing.
One is transforming weak sharp minima to an optimization problem; another is using conjugate functions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com