With the improved Wolfe line search, the global convergence of Dai-Kou type conjugate gradient methods was guaranteed.
We provide a discussion of when random search methods are guaranteed to converge almost surely to a globally optimal system design, as well as a description of desirable features such methods should have in order to yield attractive empirical performance.
One of the well-known results demonstrates that the sparsity-based methods such as ℓ1 minimization and greedy methods, are guaranteed to perfectly recover the s-sparse vectors when μ Φ < 1 2 s [6].
As mentioned earlier, for a linear neuron, reverse correlation (RC) methods are guaranteed to produce an unbiased estimate of a neuron's true underlying STRF regardless of the stimulus statistics [36].
MCMC methods are guaranteed to produce chains that converge, given an infinitely long chain; in practice, however, analysts must settle for finitely long chains.
Various approaches have been proposed [ 20, 34, 35], but since the range and distribution of network weights is method-dependent, a fair comparison of methods is guaranteed only for individually optimized thresholds, for example, maximized F1 score.
Tree error impacted by evolutionary diameter: Phylogeny estimation is typically studied in the context of a Markov model of sequence evolution; simulations of sequence evolution under these models are used to understand the model conditions that impact accuracy of phylogeny estimation methods, and theoretical results establish conditions under which methods are guaranteed to be accurate.
But when prices are falling, the commission's method is guaranteed to mischaracterize the market.
The proposed method is guaranteed to find the optimum solution.
Furthermore, for the first time, the proposed method is guaranteed to converge to global optimal settings.
The method is guaranteed to find all feasible controllers of given structure in the search domain.
