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- such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection...
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- first part. Chapter 2 studies the local convergence of Newton’s method, inexact Newton methods ... region methods, which are used to globalize convergence, i.e., remove the restriction that the starting ... studied in chapter 4. A local convergence analysis is provided and implementation details are discussed...
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- different values of the tuning parameter. Convergence of glasso can be tricky; the converged precision ... estimated covariance, and occasionally it fails to converge with warm starts. In this paper...
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- iteration. For the iterative algorithms a convergence tolerance is hard-coded (in function mft_tolerance...
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- Convergence properties of the Nelder--Mead simplex method in low dimensions The Nelder--Mead simplex ... Nelder--Mead algorithm. This paper presents convergence properties of the Nelder--Mead algorithm applied ... dimensions 1 and 2. We prove convergence to a minimizer for dimension 1, and various ... limited convergence results for dimension 2. A counterexample of McKinnon gives a family of strictly...
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- pointwise consistent”--they are guaranteed to converge almost certainly to correct information about the true...
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- previous schemes in robustness and accuracy. The convergence rate is shown to be independent ... time derivative term, albeit a different convergence history may occur. Moreover, the new scheme...
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- whose associated monotone sequence of optimal values converges to the global optimum...
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- close connection with an associated affine invariant convergence analysis. Part of these algorithms are presented...
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- construction, smoothing parameter selection, computation, and asymptotic convergence. Most of the computational and data analytical...
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- simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov...
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- each other, moreover for $alpha =0.8$ the convergent order in space is confirmed...
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- dominant physical mechanism. The lack of convergence with spatial refinement, or convergence to a solution...
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- discussed. We also analyze the theoretical convergence properties of the algorithm and provide a regret ... bound on the convergence rate that is comparable to the best known results under...
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- HOMPACK: A suite of codes for globally convergent homotopy algorithms. There are algorithms for finding ... nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with...
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- problems in terms of the speed of convergence, costs of every iteration, and memory requirements ... that our method is more robust and converges almost two times faster...
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- provides a convenient way to guarantee the convergence of a solution. This book consists...
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- operations diversify the population and improve the convergence performance. The parameter adaptation automatically updates ... algorithms from the literature in terms of convergence performance for a set of 20 benchmark...
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- which is globally convergent whenever the line search fulfills the Wolfe conditions. This article studies ... convergence behavior of the algorithm; extensive numerical tests and comparisons with other methods for large...
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- Newton method, the SQP algorithm converges very rapidly, meaning that it requires few iterations (hence...